{"id":61459,"date":"2025-11-11T01:53:06","date_gmt":"2025-11-11T00:53:06","guid":{"rendered":"https:\/\/virtual-routes.org\/?page_id=61459"},"modified":"2025-11-17T23:01:43","modified_gmt":"2025-11-17T22:01:43","slug":"ai-in-apararea-cibernetica","status":"publish","type":"page","link":"https:\/\/virtual-routes.org\/ro\/ai-in-cybersecurity-toolkit\/ai-in-cyber-defence\/","title":{"rendered":"AI \u00een ap\u0103rarea cibernetic\u0103"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"61459\" class=\"elementor elementor-61459\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6c36906 e-flex e-con-boxed e-con e-parent\" data-id=\"6c36906\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-969c1a1 e-con-full e-flex e-con e-child\" data-id=\"969c1a1\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div data-dce-title-color=\"#0E093A\" class=\"elementor-element elementor-element-7ed3c90 elementor-widget elementor-widget-heading\" data-id=\"7ed3c90\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">AI in Cyber Defence<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7a0a132 elementor-widget elementor-widget-text-editor\" data-id=\"7a0a132\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>How AI changes cyber defence across the cyber incident lifecycle<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-df4d47b elementor-absolute dce_masking-none elementor-invisible elementor-widget elementor-widget-image\" data-id=\"df4d47b\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;,&quot;_animation&quot;:&quot;slideInRight&quot;}\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img alt=\"\" loading=\"lazy\" decoding=\"async\" width=\"767\" height=\"773\" src=\"https:\/\/virtual-routes.org\/wp-content\/uploads\/2024\/11\/white-stair.svg\" class=\"attachment-full size-full wp-image-10938\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4a69b68 e-flex e-con-boxed e-con e-parent\" data-id=\"4a69b68\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;sticky&quot;:&quot;top&quot;,&quot;sticky_on&quot;:[&quot;desktop&quot;,&quot;tablet&quot;,&quot;mobile&quot;],&quot;sticky_offset&quot;:0,&quot;sticky_effects_offset&quot;:0,&quot;sticky_anchor_link_offset&quot;:0}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<a class=\"elementor-element elementor-element-e5fc1cf e-con-full e-flex e-con e-child\" data-id=\"e5fc1cf\" data-element_type=\"container\" data-e-type=\"container\" href=\"https:\/\/virtual-routes.org\/ai-in-cybersecurity-toolkit\/\">\n\t\t\t\t<div class=\"elementor-element elementor-element-86ab8e5 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"86ab8e5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-heading-title elementor-size-default\">Home<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/a>\n\t\t<a class=\"elementor-element elementor-element-c6e7cb4 e-con-full e-flex e-con e-child\" data-id=\"c6e7cb4\" data-element_type=\"container\" data-e-type=\"container\" href=\"https:\/\/virtual-routes.org\/ai-in-cybersecurity-toolkit\/ai-in-cyber-defence\/\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7a93047 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"7a93047\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-heading-title elementor-size-default\">AI in Cyber Defence<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/a>\n\t\t<a class=\"elementor-element elementor-element-bc6c7e0 e-con-full e-flex e-con e-child\" data-id=\"bc6c7e0\" data-element_type=\"container\" data-e-type=\"container\" href=\"https:\/\/virtual-routes.org\/ai-in-cybersecurity-toolkit\/ai-in-cyber-offence\/\">\n\t\t\t\t<div class=\"elementor-element elementor-element-27f751c elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"27f751c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-heading-title elementor-size-default\">AI in Cyber Offence<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0eb59e1 p e-flex e-con-boxed e-con e-child\" data-id=\"0eb59e1\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d3fade3 elementor-widget elementor-widget-text-editor\" data-id=\"d3fade3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Cyber defence aims to protect systems, networks, and data against infiltration, disruption, or destruction. The <a href=\"https:\/\/www.enisa.europa.eu\/publications\/best-practices-for-cyber-crisis-management\">cyber incident lifecycle<\/a> provides a useful way to understand cyber defence, breaking it down into four phases:<\/p><ul><li><strong>Prevention:<\/strong> preventing and reducing the risk of incidents and minimising their potential effects.<\/li><li><strong>Preparedness:<\/strong> developing plans, tools, and capabilities to support effective response.<\/li><li><strong>Response:<\/strong> stemming the incident and preventing further damage.<\/li><li><strong>Recovery:<\/strong> restoring operations quickly and returning to a normal or stronger level of security.<\/li><\/ul><p>\u00a0<\/p><p style=\"margin-top: -22px;\">Artificial intelligence (AI) has become relevant across all four phases. Unlike traditional tools that fit neatly into one step, many AI capabilities cut across the lifecycle: the same technique that supports preparedness can also enable faster response or aid recovery. This integration makes AI both powerful and challenging to classify: its value lies not only in improving individual tasks but in linking the phases together more seamlessly.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-a607854 e-flex e-con-boxed e-con e-parent\" data-id=\"a607854\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-31fca9f e-con-full main-phase-container e-flex e-con e-child\" data-id=\"31fca9f\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-ca621e9 e-con-full e-flex e-con e-child\" data-id=\"ca621e9\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9a88f20 elementor-widget elementor-widget-heading\" data-id=\"9a88f20\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Prevention<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-303cf24 elementor-view-stacked elementor-absolute elementor-shape-circle elementor-widget elementor-widget-icon\" data-id=\"303cf24\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"icon.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-icon-wrapper\">\n\t\t\t<div class=\"elementor-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-arrow-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm-28.9 143.6l75.5 72.4H120c-13.3 0-24 10.7-24 24v16c0 13.3 10.7 24 24 24h182.6l-75.5 72.4c-9.7 9.3-9.9 24.8-.4 34.3l11 10.9c9.4 9.4 24.6 9.4 33.9 0L404.3 273c9.4-9.4 9.4-24.6 0-33.9L271.6 106.3c-9.4-9.4-24.6-9.4-33.9 0l-11 10.9c-9.5 9.6-9.3 25.1.4 34.4z\"><\/path><\/svg>\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2db387b e-con-full e-flex e-con e-child\" data-id=\"2db387b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2391c85 elementor-widget elementor-widget-heading\" data-id=\"2391c85\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Preparedness<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a92426 elementor-view-stacked elementor-absolute elementor-shape-circle elementor-widget elementor-widget-icon\" data-id=\"8a92426\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"icon.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-icon-wrapper\">\n\t\t\t<div class=\"elementor-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-arrow-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm-28.9 143.6l75.5 72.4H120c-13.3 0-24 10.7-24 24v16c0 13.3 10.7 24 24 24h182.6l-75.5 72.4c-9.7 9.3-9.9 24.8-.4 34.3l11 10.9c9.4 9.4 24.6 9.4 33.9 0L404.3 273c9.4-9.4 9.4-24.6 0-33.9L271.6 106.3c-9.4-9.4-24.6-9.4-33.9 0l-11 10.9c-9.5 9.6-9.3 25.1.4 34.4z\"><\/path><\/svg>\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0d9534e e-con-full e-flex e-con e-child\" data-id=\"0d9534e\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a6a6575 elementor-widget elementor-widget-heading\" data-id=\"a6a6575\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Response<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4087432 elementor-view-stacked elementor-absolute elementor-shape-circle elementor-widget elementor-widget-icon\" data-id=\"4087432\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"icon.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-icon-wrapper\">\n\t\t\t<div class=\"elementor-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-arrow-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm-28.9 143.6l75.5 72.4H120c-13.3 0-24 10.7-24 24v16c0 13.3 10.7 24 24 24h182.6l-75.5 72.4c-9.7 9.3-9.9 24.8-.4 34.3l11 10.9c9.4 9.4 24.6 9.4 33.9 0L404.3 273c9.4-9.4 9.4-24.6 0-33.9L271.6 106.3c-9.4-9.4-24.6-9.4-33.9 0l-11 10.9c-9.5 9.6-9.3 25.1.4 34.4z\"><\/path><\/svg>\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-839c49e e-con-full e-flex e-con e-child\" data-id=\"839c49e\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3295fd5 elementor-widget elementor-widget-heading\" data-id=\"3295fd5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Recovery<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6f42479 e-con-full attack-surface-mapping clickable e-flex e-con e-child\" data-id=\"6f42479\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div data-dce-title-color=\"#0E093A\" class=\"elementor-element elementor-element-c73cfa4 elementor-widget-mobile__width-auto sticky-text elementor-widget__width-auto elementor-widget elementor-widget-heading\" data-id=\"c73cfa4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Attack surface mapping<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ff904ab e-con-full e-flex e-con e-child\" data-id=\"ff904ab\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d00fac6 e-con-full code-scanning-evaluation clickable e-flex e-con e-child\" data-id=\"d00fac6\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cbcf670 sticky-text elementor-widget elementor-widget-heading\" data-id=\"cbcf670\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Code scanning<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-eea2e6c e-con-full e-flex e-con e-child\" data-id=\"eea2e6c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7f7e850 e-con-full e-flex e-con e-child\" data-id=\"7f7e850\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4fa3d2e e-con-full data-summarisation clickable e-flex e-con e-child\" data-id=\"4fa3d2e\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4a150e8 sticky-text elementor-widget elementor-widget-heading\" data-id=\"4a150e8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data summarisation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1d2c163 e-con-full data-classification clickable e-flex e-con e-child\" data-id=\"1d2c163\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b697400 sticky-text elementor-widget elementor-widget-heading\" data-id=\"b697400\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data classification<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7c80cc5 e-con-full e-flex e-con e-child\" data-id=\"7c80cc5\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-743b8e3 e-con-full e-flex e-con e-child\" data-id=\"743b8e3\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-bdedb58 e-con-full anomaly-detection clickable e-flex e-con e-child\" data-id=\"bdedb58\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e3f59ea sticky-text elementor-widget elementor-widget-heading\" data-id=\"e3f59ea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Anomaly detection<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-549b0c9 e-con-full e-flex e-con e-child\" data-id=\"549b0c9\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5879f26 e-con-full writing-analysis clickable e-flex e-con e-child\" data-id=\"5879f26\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9f69ecd sticky-text elementor-widget elementor-widget-heading\" data-id=\"9f69ecd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Writing and analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-834de9f e-con-full synthetic-data clickable e-flex e-con e-child\" data-id=\"834de9f\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2d005a9 sticky-text elementor-widget elementor-widget-heading\" data-id=\"2d005a9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Synthetic data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-eb7d2bd e-con-full e-flex e-con e-child\" data-id=\"eb7d2bd\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1f2cf9a e-con-full iam clickable e-flex e-con e-child\" data-id=\"1f2cf9a\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-fbb11d8 sticky-text elementor-widget elementor-widget-heading\" data-id=\"fbb11d8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Identity and access management<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-40b7c74 e-con-full e-flex e-con e-child\" data-id=\"40b7c74\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-01cfe51 e-con-full iam clickable e-flex e-con e-child\" data-id=\"01cfe51\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1c50afa sticky-text elementor-widget elementor-widget-heading\" data-id=\"1c50afa\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Identity and access management<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-58a0990 e-con-full e-flex e-con e-child\" data-id=\"58a0990\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-31ce5a8 e-con-full e-flex e-con e-child\" data-id=\"31ce5a8\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d0508bb e-con-full log-analysis clickable e-flex e-con e-child\" data-id=\"d0508bb\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8b52d2c sticky-text elementor-widget elementor-widget-heading\" data-id=\"8b52d2c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Log analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8950b27 e-con-full e-flex e-con e-child\" data-id=\"8950b27\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8ae99fb e-con-full malware-analysis clickable e-flex e-con e-child\" data-id=\"8ae99fb\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b56a73c sticky-text elementor-widget elementor-widget-heading\" data-id=\"b56a73c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Malware analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-a65861b e-con-full e-flex e-con e-child\" data-id=\"a65861b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8855a07 e-con-full training-labs clickable e-flex e-con e-child\" data-id=\"8855a07\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e3e3eef training-labs clickable elementor-widget elementor-widget-heading\" data-id=\"e3e3eef\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Training and Labs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-77fa5b0 e-con-full e-flex e-con e-child\" data-id=\"77fa5b0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8fcc7f0 e-con-full training-labs clickable e-flex e-con e-child\" data-id=\"8fcc7f0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ceafbc7 elementor-widget elementor-widget-heading\" data-id=\"ceafbc7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Training and Labs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-259dc75 e-flex e-con-boxed e-con e-parent\" data-id=\"259dc75\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f52437e elementor-widget elementor-widget-html\" data-id=\"f52437e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<script>\n(function() {\n    'use strict';\n    \n    if (typeof window === 'undefined' || !window.requestAnimationFrame) {\n        return;\n    }\n    \n    const stickyElements = document.querySelectorAll('.sticky-text');\n    \n    if (!stickyElements || stickyElements.length === 0) {\n        return;\n    }\n    \n    const elementsData = [];\n    const BUFFER = 30;\n    let rafId = null;\n    let isRunning = false;\n    \n    stickyElements.forEach((element) => {\n        if (!element || 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elementWidth = element.offsetWidth || 0;\n                const parentWidth = parent.offsetWidth || 0;\n                \n                if (parentLeft < 0) {\n                    const targetOffset = -parentLeft + originalLeft;\n                    const maxOffset = Math.max(0, parentWidth - elementWidth - BUFFER);\n                    const finalOffset = Math.max(0, Math.min(targetOffset, maxOffset));\n                    \n                    element.style.position = 'relative';\n                    element.style.left = finalOffset + 'px';\n                } else {\n                    element.style.position = '';\n                    element.style.left = '';\n                }\n            });\n        } catch (error) {\n            isRunning = false;\n            if (rafId) {\n                cancelAnimationFrame(rafId);\n            }\n            return;\n        }\n        \n        rafId = requestAnimationFrame(updateLoop);\n    }\n    \n    function startMonitoring() {\n        if (isRunning) {\n            return;\n        }\n        isRunning = true;\n        rafId = requestAnimationFrame(updateLoop);\n    }\n    \n    function stopMonitoring() {\n        isRunning = false;\n        if (rafId) {\n            cancelAnimationFrame(rafId);\n            rafId = null;\n        }\n    }\n    \n    if (document.readyState === 'loading') {\n        document.addEventListener('DOMContentLoaded', startMonitoring);\n    } else {\n        startMonitoring();\n    }\n    \n    window.addEventListener('beforeunload', stopMonitoring);\n    \n    if (typeof document.hidden !== 'undefined') {\n        document.addEventListener('visibilitychange', function() {\n            if (document.hidden) {\n                stopMonitoring();\n            } else {\n                startMonitoring();\n            }\n        });\n    }\n})();\n<\/script>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-91dd04e pb-0 e-flex e-con-boxed e-con e-child\" data-id=\"91dd04e\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7019a6d elementor-widget elementor-widget-text-editor\" data-id=\"7019a6d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In the sections that follow, we examine concrete AI applications for cyber defense, showing how they map onto different phases of the incident lifecycle and, in many cases, span several at once.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-73dfa464 e-flex e-con-boxed e-con e-parent\" data-id=\"73dfa464\" data-element_type=\"container\" data-e-type=\"container\" id=\"tab-activator\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div data-dce-background-color=\"#FFFFFF00\" class=\"elementor-element elementor-element-6e8d52db e-con-full e-flex e-con e-child\" data-id=\"6e8d52db\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-14be7a26 e-n-tabs-mobile elementor-widget elementor-widget-n-tabs\" data-id=\"14be7a26\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"nested-tabs.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"e-n-tabs\" data-widget-number=\"348027430\" aria-label=\"File. Deschizi elementele cu tasta Enter sau Spa\u021biu, le \u00eenchizi cu Esc \u0219i navighezi folosind tastele s\u0103ge\u021bi.\">\n\t\t\t<div class=\"e-n-tabs-heading\" role=\"tablist\">\n\t\t\t\t\t<button id=\"attack-surface-mapping\" data-tab-title-id=\"e-n-tab-title-3480274301\" class=\"e-n-tab-title\" aria-selected=\"true\" data-tab-index=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"e-n-tab-content-3480274301\" style=\"--n-tabs-title-order: 1;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tAttack surface mapping\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"code-scanning-evaluation\" data-tab-title-id=\"e-n-tab-title-3480274302\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274302\" style=\"--n-tabs-title-order: 2;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tCode scanning and evaluation\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"data-summarisation\" data-tab-title-id=\"e-n-tab-title-3480274303\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"3\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274303\" style=\"--n-tabs-title-order: 3;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tData summarisation\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"data-classification\" data-tab-title-id=\"e-n-tab-title-3480274304\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"4\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274304\" style=\"--n-tabs-title-order: 4;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tData classification\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"anomaly-detection\" data-tab-title-id=\"e-n-tab-title-3480274305\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"5\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274305\" style=\"--n-tabs-title-order: 5;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tEndpoint or network anomaly detection\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"writing-analysis\" data-tab-title-id=\"e-n-tab-title-3480274306\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"6\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274306\" style=\"--n-tabs-title-order: 6;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tGeneral writing and data gathering\/analysis tasks\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"synthetic-data\" data-tab-title-id=\"e-n-tab-title-3480274307\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"7\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274307\" style=\"--n-tabs-title-order: 7;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tGenerating synthetic data\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"iam\" data-tab-title-id=\"e-n-tab-title-3480274308\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"8\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274308\" style=\"--n-tabs-title-order: 8;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tIdentity and access management (IAM)\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"log-analysis\" data-tab-title-id=\"e-n-tab-title-3480274309\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"9\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-3480274309\" style=\"--n-tabs-title-order: 9;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tLog analysis\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"malware-analysis\" data-tab-title-id=\"e-n-tab-title-34802743010\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"10\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-34802743010\" style=\"--n-tabs-title-order: 10;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tMalware analysis\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"training-labs\" data-tab-title-id=\"e-n-tab-title-34802743011\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"11\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-34802743011\" style=\"--n-tabs-title-order: 11;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tTraining and labs\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"e-n-tab-title-34802743012\" data-tab-title-id=\"e-n-tab-title-34802743012\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"12\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-34802743012\" style=\"--n-tabs-title-order: 12;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tDiscussion questions\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"e-n-tab-title-34802743013\" data-tab-title-id=\"e-n-tab-title-34802743013\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"13\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-34802743013\" style=\"--n-tabs-title-order: 13;\">\n\t\t\t\t\t<span class=\"e-n-tab-icon\">\n\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t<\/span>\n\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tBibliography\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t\t<\/div>\n\t\t\t<div class=\"e-n-tabs-content\">\n\t\t\t\t<div id=\"e-n-tab-content-3480274301\" role=\"tabpanel\" aria-labelledby=\"attack-surface-mapping\" data-tab-index=\"1\" style=\"--n-tabs-title-order: 1;\" class=\"e-active elementor-element elementor-element-5e5c189b e-con-full e-flex e-con e-child\" data-id=\"5e5c189b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-64f20660 e-con-full e-flex e-con e-child\" data-id=\"64f20660\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4fae0df0 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"4fae0df0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Attack surface mapping<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-79cc8aff elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"79cc8aff\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-77d14d7e elementor-widget elementor-widget-text-editor\" data-id=\"77d14d7e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Attack surface mapping identifies all the assets, entry points, and vulnerabilities an adversary could exploit in an attack. It provides defenders with visibility into their exposure and helps prioritise what to secure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-656111a9 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"656111a9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes attack surface mapping:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-531f42db elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"531f42db\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div>AI transforms attack surface mapping by automating large-scale scans of networks and assets, dramatically reducing manual effort. With advanced pattern recognition, it can detect hidden or forgotten endpoints that traditional methods often miss. AI systems can update maps continuously as infrastructures evolve, reducing blind spots and ensuring defenders maintain an accurate, real-time picture of their environment.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-4ba4a5ef elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"4ba4a5ef\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Prevention.<\/strong> Reduces exposures before attackers exploit them.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-1b049691 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"1b049691\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Maintains an updated view of infrastructure for incident planning.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-46eb4add e-con-full e-flex e-con e-child\" data-id=\"46eb4add\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4612b0e4 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"4612b0e4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: Use of LLMs for asset discovery in critical infrastructure<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-447f550a elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"447f550a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2025, <a href=\"https:\/\/doi.org\/10.3390\/electronics14163267\">Luigi Coppolino et al <\/a>published a study showing how large language models (LLMs) can improve the discovery of assets in critical infrastructures. Traditional tools such as Nmap or industrial security platforms either risk disrupting sensitive systems through active scans or fail to detect hidden devices when relying only on passive monitoring.<\/p><p>The researchers proposed an LLM-based &#8220;Mixture of Experts&#8221; framework that combines data from passive traffic observation, carefully limited active probing and physical signals such as electromagnetic emissions. Specialised LLM agents then interpret this data: one focuses on industrial protocols, another on vulnerabilities in IT\/OT networks, and another on system architecture and dependencies.<\/p><p>The system can also draw on external intelligence sources (such as MITRE ATT&amp;CK or CVE databases) to identify weaknesses and recommend security measures. In tests on a simulated industrial network, it successfully classified assets like programmable logic controllers, robotic arms, and printers, while flagging insecure practices such as unencrypted Modbus traffic.<\/p><p>Such an approach turns attack surface mapping into an adaptive and context-aware process that provides real-time visibility and reduces the risks of traditional scanning. By lowering the technical barriers for defenders, it enables more comprehensive monitoring and strengthens the overall security posture of critical infrastructure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-314b18b e-con-full e-flex e-con e-child\" data-id=\"314b18b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ebd483e elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"ebd483e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"ebd483e\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-ebd483e\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-3f6e4dc e-con-full e-flex e-con e-child\" data-id=\"3f6e4dc\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-ebd483e\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-64b8356 e-con-full e-flex e-con e-child\" data-id=\"64b8356\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e2562f7 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"e2562f7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Impact of AI for threat detection - <a href=\"https:\/\/doi.org\/10.1007\/979-8-8688-0947-7_3\">\"AI for Defense\" (Donnie W. Wendt 2024)<\/a><br> The chapter shows how AI has advanced threat detection and triage, where machine learning models process vast amounts of heterogeneous data to identify potential attacks. Results highlight how early applications in the 2000s-2010s focused on malware, intrusion, and spam detection, demonstrating AI's strength in analysing large datasets and improving existing detection systems while incrementally enhancing longstanding cybersecurity functions.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Next-generation threat detection - <a href=\"https:\/\/doi.org\/10.56726\/IRJMETS32644\">\"Revolutionizing Cybersecurity: Unleashing the Power of Artificial Intelligence and Machine Learning\" (Manoharan &amp; Sarker 2022)<\/a><br>The paper shows how AI and machine learning are revolutionising threat detection, enabling organisations to spot anomalies, analyse behavioural patterns, and predict potential attacks. Results highlight how techniques such as NLP for extracting threat intelligence and deep learning for pattern recognition can automate detection and response, while real-world case studies confirm their effectiveness.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274302\" role=\"tabpanel\" aria-labelledby=\"code-scanning-evaluation\" data-tab-index=\"2\" style=\"--n-tabs-title-order: 2;\" class=\" elementor-element elementor-element-102f5cf2 e-con-full e-flex e-con e-child\" data-id=\"102f5cf2\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-2091fc35 e-con-full e-flex e-con e-child\" data-id=\"2091fc35\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-20a4d496 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"20a4d496\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Code scanning and evaluation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b5b7f0c elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"b5b7f0c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2c82968c elementor-widget elementor-widget-text-editor\" data-id=\"2c82968c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Code scanning reviews source code to detect vulnerabilities, insecure libraries, or poor security practices before they can be exploited.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2696f42d elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"2696f42d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes code scanning and evaluation:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-34e6457 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"34e6457\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI accelerates vulnerability detection by highlighting insecure functions and identifying risky coding patterns learned from past exploits. It also offers automated remediation suggestions, supporting developers in writing more secure code and reducing the window of opportunity for attackers.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-1f8901c5 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"1f8901c5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Prevention.<\/strong> Fixes weaknesses before attackers discover them.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-210bebc elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"210bebc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Strengthens baseline security posture for incident readiness.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-5de58f28 e-con-full e-flex e-con e-child\" data-id=\"5de58f28\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-25204f5 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"25204f5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: Use of LLMs for code scanning and secure development<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-59f93f5e elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"59f93f5e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2025, <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2504.20814\">Belozerov et al <\/a>investigated how large language models can support secure coding practices. Their study tested ChatGPT against the DevGPT dataset, which contained real developer code alongside known vulnerabilities flagged by static scanners. Out of 32 confirmed vulnerabilities, ChatGPT correctly detected 18 and even suggested fixes for 17 of them.<\/p><p>The results show how AI can reduce manual effort in code review, help triage risky coding patterns and provide automated remediation suggestions. This has the potential to scale secure coding practices and shorten the time window in which vulnerabilities remain exploitable.<\/p><p>At the same time, the study emphasised important limitations: ChatGPT occasionally produced overconfident but incorrect outputs, introduced new flaws when attempting fixes and was less reliable than static analysis or expert human review. A key takeaway from this study is that AI can be a powerful assistant in code evaluation, but only when combined with traditional tools and proper oversight.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-bd5bc13 e-con-full e-flex e-con e-child\" data-id=\"bd5bc13\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cfe9a09 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"cfe9a09\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"cfe9a09\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-cfe9a09\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-c151b76 e-con-full e-flex e-con e-child\" data-id=\"c151b76\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-cfe9a09\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-bdd0b76 e-con-full e-flex e-con e-child\" data-id=\"bdd0b76\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ca347b6 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"ca347b6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Automated code review - <a href=\"https:\/\/www.researchgate.net\/publication\/394286736_A_Review_of_Applying_AI_for_Cybersecurity_Opportunities_Risks_and_Mitigation_Strategies\">\"A Review of Applying AI for Cybersecurity: Opportunities, Risks, and Mitigation Strategies\" (Ndibe &amp; Ufomba 2024)<\/a><br> The paper shows how AI and large language models can support automated code reviews and vulnerability assessments, helping organisations proactively detect weaknesses in source code and reduce response times. Results also highlight risks such as insecure AI-generated code, underscoring the need for human oversight and governance frameworks.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Interpretable deep learning for vulnerability detection - <a href=\"https:\/\/doi.org\/10.1145\/3468264.3468597\">\"Vulnerability Detection with Fine-grained Interpretations\" (Li et al. 2021)<\/a><br> This paper presents IVDetect, a deep learning model that detects vulnerabilities in codes and pinpoints the specific statements and dependencies responsible. IVDetect improves accuracy over state-of-the-art tools and provides fine-grained explanations. Findings show substantial gains in detection performance and more precise identification of vulnerable code, supporting both automated analysis and developer remediation.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Multilingual code vulnerability detection - <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2508.11710\">\"Code Vulnerability Detection Across Different Programming Languages with AI Models\" (Humran &amp; Sonmez 2025)<\/a><br> This paper investigates transformer-based models, including CodeBERT and CodeLlama, for detecting vulnerabilities across multiple programming languages. By fine-tuning on diverse datasets, the models capture both syntax and semantics, achieving up to 97% accuracy. The study also incorporates ensemble methods and explainable AI to reduce false positives and improve developer trust. It demonstrates that AI models can outperform traditional static analysers in cross-language settings, though challenges remain in robustness, precision and deployment readiness.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274303\" role=\"tabpanel\" aria-labelledby=\"data-summarisation\" data-tab-index=\"3\" style=\"--n-tabs-title-order: 3;\" class=\" elementor-element elementor-element-12cf6159 e-con-full e-flex e-con e-child\" data-id=\"12cf6159\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-4e4a8ee3 e-con-full e-flex e-con e-child\" data-id=\"4e4a8ee3\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2ef820e7 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"2ef820e7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data summarisation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-17f46d3d elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"17f46d3d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-67670e0f elementor-widget elementor-widget-text-editor\" data-id=\"67670e0f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Data summarisation condenses large volumes of technical data (e.g., logs, reports, and threat intelligence) into accessible insights.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-167eb8ed elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"167eb8ed\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes data summarisation:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a0a8def elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"5a0a8def\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI reduces cognitive overload by transforming raw and unstructured information into actionable intelligence. It can identify recurring patterns or anomalies across fragmented datasets. It can also generate plain language reports for non-specialists. AI therefore makes information easier to consume, communicate, and act upon.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-34ec9b90 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"34ec9b90\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Helps digest threat intelligence and plan more effectively.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-26574200 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"26574200\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Response.<\/strong> Streamlines situational awareness in real time.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-1bf0296c elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"1bf0296c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Recovery.<\/strong> Produces summaries and reports for lessons learned.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-5d710aca e-con-full e-flex e-con e-child\" data-id=\"5d710aca\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-730d8f43 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"730d8f43\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: AI for log summarisation and situational awareness<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-237f8832 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"237f8832\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2024, <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2403.17160\">Balasubramanian et al <\/a>introduced CYGENT, a conversational agent powered by GPT-3 that can analyse and summarise system logs. Instead of requiring analysts to sift through thousands of raw log entries, CYGENT condenses them into short, human-readable outputs that highlight key events and anomalies.<\/p><p>In evaluations, CYGENT outperformed other large language models in producing clear and actionable summaries. The system reduced cognitive overload, supported situational awareness during live incidents, and enabled faster decision-making.<\/p><p>This case illustrates how AI can transform raw, technical data into accessible intelligence. By making logs easier to interpret, it helps defenders prepare more effectively, respond more quickly, and recover with better documentation after incidents.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-642d19a e-con-full e-flex e-con e-child\" data-id=\"642d19a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-615af78 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"615af78\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"615af78\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-615af78\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-d3b225a e-con-full e-flex e-con e-child\" data-id=\"d3b225a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-615af78\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-203b012 e-con-full e-flex e-con e-child\" data-id=\"203b012\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-06f217f elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"06f217f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">CTI summarisation datasets - <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2408.06576\">\"CTISum: A New Benchmark Dataset for Cyber Threat Intelligence Summarisation\" (Peng et al. 2024)<\/a><br> The paper introduces CTISum, a dataset for summarising cyber threat intelligence (CTI) reports, allowing for the summarisation of complex intelligence reports to help defenders plan and capture lessons learned more effectively.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">TTP extraction - <a href=\"https:\/\/doi.org\/10.1145\/3696427\">\"TTPXHunter: Actionable Threat Intelligence Extraction as TTPs from Finished Cyber Threat Reports\" (Rani et al. 2024)<\/a> <br> The paper proposes TTPXHunter, an NLP-based tool that extracts attacker tactics, techniques and procedures (TTPs) from threat reports to understand their modus operandi, transforming unstructured intelligence into structured, actionable summaries.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">NLP for incident analysis - <a href=\"https:\/\/www.researchgate.net\/publication\/382917950_Natural_Language_Processing_for_Cybersecurity_Incident_Analysis\">\"Natural Language Processing for Cybersecurity Incident Analysis\" (Ogundairo &amp; Broklyn, 2024)<\/a> <br>The paper surveys NLP applications for analysing unstructured data sources, with NLP techniques (e.g., entity recognition, sentiment analysis, summarisation, chatbot-based triage). The paper finds that NLP can automate incident reporting and threat intelligence summaries, reducing response times and improving post-incident documentation.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274304\" role=\"tabpanel\" aria-labelledby=\"data-classification\" data-tab-index=\"4\" style=\"--n-tabs-title-order: 4;\" class=\" elementor-element elementor-element-2dfdf682 e-con-full e-flex e-con e-child\" data-id=\"2dfdf682\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-62a0ac0c e-con-full e-flex e-con e-child\" data-id=\"62a0ac0c\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-74348399 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"74348399\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data classification<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cd12159 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"cd12159\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5451aafa elementor-widget elementor-widget-text-editor\" data-id=\"5451aafa\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Data classification organises information according to its sensitivity or compliance requirements, ensuring that critical assets receive appropriate protection.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5f91a7d0 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"5f91a7d0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes data classification:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2ab2deb0 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"2ab2deb0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI uses natural language processing to automatically tag sensitive content and detect misclassified or exposed data at scale.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-3e7eb85f elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"3e7eb85f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Prevention.<\/strong> Reduces accidental exposure of sensitive data.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-295f104a elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"295f104a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Supports compliance.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-1946bb24 e-con-full e-flex e-con e-child\" data-id=\"1946bb24\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-19abb30e elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"19abb30e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: AI for sensitive data classification<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-71ff510c elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"71ff510c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2024, <a href=\"https:\/\/ceur-ws.org\/Vol-3643\/paper3.pdf\">De Renzis et al <\/a>investigated how large language models could be used to improve the classification of sensitive information. A central challenge in this area is that real personal data cannot always be used for training because of privacy risks. The authors proposed generating synthetic training data that still reflects the patterns of sensitive categories, such as health, politics, or religion.<\/p><p>Their approach enabled the training of accurate classifiers without exposing actual user data, demonstrating how AI can help organisations comply with regulations such as GDPR while scaling up their ability to detect and protect sensitive information. This case illustrates how AI strengthens both prevention (by reducing accidental data exposure) and preparedness (by supporting compliance frameworks). At the same time, it underlines the importance of governance and validation to ensure synthetic data and resulting models remain representative and reliable.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0f80863 e-con-full e-flex e-con e-child\" data-id=\"0f80863\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-aca4f78 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"aca4f78\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"aca4f78\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-aca4f78\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-4b66049 e-con-full e-flex e-con e-child\" data-id=\"4b66049\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-aca4f78\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-f8c541c e-con-full e-flex e-con e-child\" data-id=\"f8c541c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-add1303 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"add1303\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Transformer-based tagging of GDPR categories - <a href=\"https:\/\/doi.org\/10.3390\/fi14080228\">\"Automatic Detection of Sensitive Data Using Transformer-Based Classifiers\" (Petrolini et al. 2022)<\/a><br> This study applies AI models to automatically flag sensitive text, covering areas such as politics, health, religion, and sexuality, within large document collections. It demonstrates that transformer-based approaches can reliably classify such data, supporting GDPR compliance and enabling large-scale and automated labelling for compliance-driven data classification.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Semantic analysis for automated sensitive data detection - <a href=\"https:\/\/doi.org\/10.1186\/s42400-018-0011-x\">\"Automated identification of sensitive data from implicit user specification (S3)\" (Yang &amp; Liang 2018)<\/a><br> This paper introduces S3, a system that identifies sensitive data in mobile apps by analysing semantics rather than relying on keywords. By learning user privacy preferences, it achieves higher accuracy than traditional tools, illustrating how AI can adapt data classification to real-world contexts. The study emphasises that the sensitivity of information depends on both application context and user preference, and that effective protection in the cloud era requires first being able to identify such data.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274305\" role=\"tabpanel\" aria-labelledby=\"anomaly-detection\" data-tab-index=\"5\" style=\"--n-tabs-title-order: 5;\" class=\" elementor-element elementor-element-7fb93d02 e-con-full e-flex e-con e-child\" data-id=\"7fb93d02\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-56c6ec e-con-full e-flex e-con e-child\" data-id=\"56c6ec\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7c5d609 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"7c5d609\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Endpoint or network anomaly detection<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c77575e elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"3c77575e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-172e19ac elementor-widget elementor-widget-text-editor\" data-id=\"172e19ac\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Anomaly detection monitors endpoints and network traffic for unusual behaviours that may indicate compromise.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7e03e927 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"7e03e927\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes endpoint and network anomaly detection:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6e110dcd elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"6e110dcd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI learns what normal activity looks like and flags deviations that might signal malicious activity. Unlike signature-based systems, it can detect more subtle intrusions that evade traditional detection. AI enables faster and more effective incident response by prioritising alerts and reducing false positives.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-6eb78ef2 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"6eb78ef2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Establishes baselines of normal activity.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-148acc6f elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"148acc6f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Response.<\/strong> Detects anomalies in real time to flag and contain attacks.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-5c840e71 e-con-full e-flex e-con e-child\" data-id=\"5c840e71\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-51f8235b elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"51f8235b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: Using AI for anomaly detection in critical systems<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3f3c9d31 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"3f3c9d31\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2024, <a href=\"https:\/\/www.researchgate.net\/publication\/386080149_AI-Driven_Anomaly_Detection_for_Proactive_Cybersecurity_and_Data_Breach_Prevention\">Nwoye and Nwagwughiagwu<\/a> examined how AI-driven anomaly detection could improve cyber defence across endpoints and networks. Using machine learning models trained on normal patterns of system behaviour and network traffic, their approach allowed them to identify subtle deviations that traditional, signature-based systems would miss, including for example early signs of insider threats and data breaches.<\/p><p>The study presented case examples from critical sectors, showing that AI-enabled anomaly detection reduced response times and helped maintain business continuity by flagging suspicious activity before it caused serious damage. The authors also acknowledged challenges, including false positives and the need for transparency in complex AI models. This case demonstrates how AI contributes to both preparedness (by establishing baselines of normal activity) and response (by detecting and prioritising anomalies in real time).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0b4e166 e-con-full e-flex e-con e-child\" data-id=\"0b4e166\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e613577 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"e613577\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"e613577\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-e613577\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-d32e1e7 e-con-full e-flex e-con e-child\" data-id=\"d32e1e7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-e613577\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-9f0a795 e-con-full e-flex e-con e-child\" data-id=\"9f0a795\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7d8c8a6 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"7d8c8a6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">GAN-based anomaly detection - <a href=\"https:\/\/arxiv.org\/abs\/2009.07769\">\"TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks\" (Geiger et al. 2020)<\/a><br> This paper presents TadGAN, an unsupervised framework that applies cycle-consistent GANs to detect anomalies in time series data. By combining reconstruction errors with critical outputs, TadGAN generates reliable anomaly scores and reduces false positives. Tested on 11 benchmark datasets from domains, it consistently outperformed state-of-the-art methods. The study shows how GANs can improve the detection of subtle temporal anomalies across diverse real-world systems.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Machine learning for infrastructure anomaly detection - <a href=\"https:\/\/dl.gi.de\/handle\/20.500.12116\/45143\">\"AI Defenders: Machine Learning Driven Anomaly Detection in Critical Infrastructures\" (Nebebe et al. 2024)<\/a><br> This paper compares machine learning models for detecting anomalies in critical infrastructure, using time-series data from a hydraulic system simulator. It distinguishes point anomalies (single outliers) from contextual anomalies (deviations only apparent in context) and compares simple interpretable models (e.g. logistic regression, decision trees) with more complex black-box models across consistent datasets. The goal is to assess which methods perform best for real-world industrial settings. The paper emphasises that while complex models may yield higher detection rates, simpler methods still offer advantages in interpretability and robustness in sensitive infrastructure domains.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274306\" role=\"tabpanel\" aria-labelledby=\"writing-analysis\" data-tab-index=\"6\" style=\"--n-tabs-title-order: 6;\" class=\" elementor-element elementor-element-33781d37 e-con-full e-flex e-con e-child\" data-id=\"33781d37\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-6ad48c1c e-con-full e-flex e-con e-child\" data-id=\"6ad48c1c\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2c54d1e2 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"2c54d1e2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">General writing and data gathering\/analysis tasks<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-54ba2073 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"54ba2073\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6dde1cb5 elementor-widget elementor-widget-text-editor\" data-id=\"6dde1cb5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Defensive operations also involve extensive writing, research, and data analysis to document incidents, inform decisions and train staff.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-26c766a elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"26c766a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes general writing and data gathering or analysis tasks:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-47ba4100 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"47ba4100\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI can draft reports, policies, and incident briefings, easing the administrative burden on analysts. It can automate open-source intelligence gathering for exercises, allowing students and professionals to focus on higher-level analysis and strategy instead of repetitive tasks.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-26aaf561 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"26aaf561\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Response.<\/strong> Supports rapid reporting and situational awareness.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-7a2e16cd elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"7a2e16cd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Recovery.<\/strong> Enables thorough post incident documentation and lessons learned.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-34606624 e-con-full e-flex e-con e-child\" data-id=\"34606624\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-17bd8f8a elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"17bd8f8a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: Automated intelligence gathering and reporting<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-36065180 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"36065180\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2024, <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2212.10388\">Gao et al<\/a>\u00a0introduced ThreatKG, an AI-powered system that automatically collects cyber threat intelligence from open sources, extracts key entities such as actors and vulnerabilities, and organises them into a structured knowledge graph. Instead of analysts manually reading through long, unstructured reports, the system provides a consolidated and searchable overview. This reduces the administrative burden of defensive operations, supports faster production of incident briefings, and improves situational awareness during active threats. By transforming fragmented information into accessible insights, ThreatKG allows staff to spend more time on interpretation and decision-making. The study illustrates how AI can reshape everyday defensive work by making intelligence gathering more efficient and actionable, while also highlighting the need for oversight to ensure accuracy and relevance.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-bb66e34 e-con-full e-flex e-con e-child\" data-id=\"bb66e34\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-37d3cdd elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"37d3cdd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"37d3cdd\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-37d3cdd\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-0da8550 e-con-full e-flex e-con e-child\" data-id=\"0da8550\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-37d3cdd\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-3017d61 e-con-full e-flex e-con e-child\" data-id=\"3017d61\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-0422b87 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"0422b87\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Governance, ethical, legal and social implications of AI in OSINT - <a href=\"https:\/\/doi.org\/10.1007\/s00146-023-01628-x\">\"Open Source Intelligence and AI: A Systematic Review\" (Ghioni et al. 2023)<\/a><br> The article reviews 571 studies on AI in OSINT, on the use of AI in open-source intelligence (OSINT), examining its governance, ethical, legal, and social implications. The review finds that AI has expanded OSINT capabilities through machine learning, data mining and visual forensics, but has also raised pressing concerns around privacy, accountability, bias, and misuse. The authors highlight gaps in regulation, oversight, and transparency, calling for stronger frameworks to ensure AI-powered OSINT supports intelligence operations without undermining rights, trust or democratic accountability.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Automated report generation - <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2310.02655\">\"AGIR: Automating Cyber Threat Intelligence Reporting with Natural Language Generation\" (Perrina et al. 2023)<\/a><br> The paper introduces AGIR, a natural language generation system that creates comprehensive CTI reports from formal entity graphs. AGIR reduces report writing time by more than 40% while maintaining high accuracy and fluency, demonstrating how AI can automate report drafting and analysis tasks, freeing analysts to focus on higher-level interpretation and strategy.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274307\" role=\"tabpanel\" aria-labelledby=\"synthetic-data\" data-tab-index=\"7\" style=\"--n-tabs-title-order: 7;\" class=\" elementor-element elementor-element-7af9ec0d e-con-full e-flex e-con e-child\" data-id=\"7af9ec0d\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-4261140f e-con-full e-flex e-con e-child\" data-id=\"4261140f\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4d77b34d elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"4d77b34d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Generating synthetic data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-59cd38ee elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"59cd38ee\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2ef7c049 elementor-widget elementor-widget-text-editor\" data-id=\"2ef7c049\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Synthetic data generation creates artificial datasets for training, testing, or simulation without exposing sensitive real world information.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4bc6fa61 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"4bc6fa61\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes generating synthetic data:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4ba9ff81 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"4ba9ff81\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI can produce realistic network traffic or malware samples for laboratory use, fill gaps where real-world data is unavailable, and safeguard privacy while enabling experimentation. This helps educators and defenders prepare for real incidents without risking sensitive data exposure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-343df702 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"343df702\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Prevention.<\/strong> Enables safe experimentation without exposing sensitive information.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-19ff8cba elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"19ff8cba\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Supports training and simulation with realistic datasets.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-60acc920 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"60acc920\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Recovery.<\/strong> Recreates attack scenarios for post-incident testing and improvement.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-39cad407 e-con-full e-flex e-con e-child\" data-id=\"39cad407\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-76c7b1c5 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"76c7b1c5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: Use of GANs for producing safe and realistic training data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-732dcaf8 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"732dcaf8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2022, <a href=\"https:\/\/doi.org\/10.1109\/GLOBECOM48099.2022.10001494\">Nukavarapu et al<\/a>\u00a0developed MirageNet, a framework that uses generative adversarial networks (GANs) to create realistic synthetic network traffic. The system can replicate patterns of DNS traffic and other protocols in a way that closely resembles real-world data, but without exposing sensitive information from live networks.<\/p><p>This innovation is important because defenders and educators often need realistic data for training, testing, and experimentation, yet cannot always use operational traffic for privacy or security reasons. MirageNet enables safe simulations that prepare analysts for real attacks while avoiding disclosure risks. The use of AI, and in this case of GANs, allows for more secure and scalable experimentation. At the same time, it remains important to validate that synthetic data truly reflects real operational conditions, ensuring that training and testing remain reliable.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9868e72 e-con-full e-flex e-con e-child\" data-id=\"9868e72\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b8a7925 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"b8a7925\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"b8a7925\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-b8a7925\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-30299e2 e-con-full e-flex e-con e-child\" data-id=\"30299e2\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-b8a7925\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-20cb3f5 e-con-full e-flex e-con e-child\" data-id=\"20cb3f5\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5c30809 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"5c30809\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Deep learning for synthetic network traffic modeling - <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2009.12740\">\"STAN: Synthetic Network Traffic Generation with Generative Neural Models\" (Xu et al. 2021)<\/a><br> The paper presents STAN (Synthetic network Traffic generation with Autoregressive Neural models), a neural architecture that models both temporal and attribute dependencies in network traffic to generate realistic datasets. Results show that anomaly detection models trained on STAN's synthetic traffic achieved near-comparable accuracy to those trained on real data, demonstrating how deep learning enables high quality synthetic datasets for preparedness training and simulation while preserving privacy.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Evaluation of synthetic traffic generation methods - <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2410.16326\">\"Synthetic Network Traffic Data Generation: A Comparative Study\" (Ammara et al., 2025)<\/a><br> The study evaluates twelve methods for synthetic traffic generation, including statistical, classical AI and generative AI approaches, using standard datasets. Results show GAN-based models provide superior fidelity and utility, while statistical methods maintain class balance but miss structural complexity.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274308\" role=\"tabpanel\" aria-labelledby=\"iam\" data-tab-index=\"8\" style=\"--n-tabs-title-order: 8;\" class=\" elementor-element elementor-element-7f370106 e-con-full e-flex e-con e-child\" data-id=\"7f370106\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-e8f1698 e-con-full e-flex e-con e-child\" data-id=\"e8f1698\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7911b5d1 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"7911b5d1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Identity and access management (IAM)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c35df68 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"5c35df68\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-693ad18 elementor-widget elementor-widget-text-editor\" data-id=\"693ad18\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Identity and access management (IAM) ensures that only authorised users have appropriate access to systems and resources.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-78f251a0 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"78f251a0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes identity and access management:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-68fc5b4c elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"68fc5b4c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI strengthens IAM by detecting anomalous login patterns that may signal credential misuse, recommending adaptive authentication policies and automating routine checks. During incidents, it can rapidly flag compromised accounts and trigger stronger controls to contain threats.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-5936f6e0 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"5936f6e0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Prevention.<\/strong> Enforces stronger authentication and reduces unauthorised access.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-7728f889 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"7728f889\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Response.<\/strong> Adapts in real time during suspected credential misuse.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-355ae3a8 e-con-full e-flex e-con e-child\" data-id=\"355ae3a8\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-267ae09c elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"267ae09c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: Detection of unusual and inappropriate access<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5f6a7b86 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"5f6a7b86\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2024, <a href=\"https:\/\/www.diva-portal.org\/smash\/get\/diva2:1943652\/FULLTEXT02.pdf\">Selling<\/a> conducted a proof-of-concept study on applying AI to IAM systems. By integrating an anomaly detection model into a live IAM platform, the system was able to flag unusual login behaviour and inappropriate access privileges. This approach allows organisations to detect compromised accounts or insider misuse more quickly and to adapt authentication policies dynamically when risks are detected. The study found clear efficiency gains while emphasising the ongoing need for human oversight to interpret flagged anomalies and avoid unnecessary disruption. AI therefore allows to strengthen everyday access control and can turn IAM into a more adaptive and proactive line of defence.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-985150d e-con-full e-flex e-con e-child\" data-id=\"985150d\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7a63260 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"7a63260\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"7a63260\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-7a63260\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-bb2356b e-con-full e-flex e-con e-child\" data-id=\"bb2356b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-7a63260\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-7e76bf7 e-con-full e-flex e-con e-child\" data-id=\"7e76bf7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-bcb67cf elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"bcb67cf\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Critical infrastructure auditing - <a href=\"https:\/\/www.researchgate.net\/publication\/390929423_AI-Powered_IAM_Audit_for_Anomaly_Detection_in_Critical_Infrastructure\">\"AI-Powered IAM Audit for Anomaly Detection in Critical Infrastructure\" (Rodriguez et al. 2025)<\/a><br> The paper proposes an AI-powered IAM audit framework that combines feature engineering, unsupervised anomaly detection and supervised classification to analyse IAM logs. On a synthetic dataset modelled after critical infrastructure, the system achieved a 92% detection rate with a false positive rate below 3%. Findings demonstrate how AI enhances IAM log auditing, enabling proactive detection of insider threats and subtle access anomalies that traditional methods often miss.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-3480274309\" role=\"tabpanel\" aria-labelledby=\"log-analysis\" data-tab-index=\"9\" style=\"--n-tabs-title-order: 9;\" class=\" elementor-element elementor-element-4da48b90 e-con-full e-flex e-con e-child\" data-id=\"4da48b90\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-f78d023 e-con-full e-flex e-con e-child\" data-id=\"f78d023\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-379f2404 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"379f2404\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Log analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-63586dde elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"63586dde\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-601ab045 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"601ab045\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Log analysis examines system and security logs to detect, investigate and understand incidents.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-140b6275 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"140b6275\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes log analysis:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1787a6dd elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"1787a6dd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI can process massive volumes of logs in real time, highlight unusual sequences of events, and generate concise summaries. This improves detection and allows for faster teaching and incident simulations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-11c22472 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"11c22472\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Establishes baselines and identifies potential weak points.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-40785102 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"40785102\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Response.<\/strong> Accelerates investigation and supports incident handling in real time.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-63b0357a elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"63b0357a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Recovery.<\/strong> Informs post-incident reviews and reporting.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-4c6b8e09 e-con-full e-flex e-con e-child\" data-id=\"4c6b8e09\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1a67221 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"1a67221\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: AI agents for log parsing and threat pattern discovery<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-64fcf552 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"64fcf552\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2025, <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2509.05306\">Karaarslan et al<\/a>\u00a0examined how AI agents could support the analysis of the extensive logs generated by Cowrie honeypots. Honeypots deliberately imitate vulnerable systems to attract attackers, but the result is an overwhelming volume of raw data that is challenging for human analysts to interpret.<\/p><p>The researchers showed that AI agents can automatically parse and summarise these logs, extracting recurring attack patterns and generating concise reports. This automation reduces manual effort, enhances situational awareness, and allows defenders to detect trends and adjust security measures more rapidly. The study illustrates how AI can transform unmanageable datasets into actionable intelligence, while also underlining the need to validate outputs carefully so that evolving or deceptive adversarial tactics are not misread.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7fab8e0 e-con-full e-flex e-con e-child\" data-id=\"7fab8e0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b71c24a elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"b71c24a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"b71c24a\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-b71c24a\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-28fdb7c e-con-full e-flex e-con e-child\" data-id=\"28fdb7c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-b71c24a\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-04be5b3 e-con-full e-flex e-con e-child\" data-id=\"04be5b3\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-77987ab elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"77987ab\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Self-supervised log analysis - <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2203.10960\">\"AI-Driven Log Analysis Using Transformer Constructs\" (Pan 2023)<\/a><br> This study explores how AI can support log analysis for incident detection and investigation. Using a Transformer model trained on normal log entries, the approach applies log augmentation for self-supervised feature learning and then fine-tunes the model with reinforcement learning on a small labelled dataset. Results indicate that this method can overcome challenges of heterogeneous log sources and scarce labelled data, showing promise for practical and real-world deployment in cybersecurity operations.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Deep learning-based log analysis for intrusion detection - <a href=\"https:\/\/doi.org\/10.1016\/j.cose.2024.104222\">\"Cyberattack event logs classification using deep learning with semantic feature analysis\" (Alzu'bi et al. 2025)<\/a><br> This study proposes a deep learning\u2013based framework using semantic vectorization and BERT embeddings to analyze event logs for intrusion detection. By categorizing logs by event and attack types with explainable AI, the approach improves detection accuracy, achieving over 99% recall and precision, and outperforms existing models.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-34802743010\" role=\"tabpanel\" aria-labelledby=\"malware-analysis\" data-tab-index=\"10\" style=\"--n-tabs-title-order: 10;\" class=\" elementor-element elementor-element-32dcb80 e-con-full e-flex e-con e-child\" data-id=\"32dcb80\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-7e5cf53 e-con-full e-flex e-con e-child\" data-id=\"7e5cf53\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-77b57bdc elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"77b57bdc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Malware analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6d506f51 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"6d506f51\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1f9b5cc2 elementor-widget elementor-widget-text-editor\" data-id=\"1f9b5cc2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Malware analysis investigates malicious software to understand its behaviour, origin and potential impact.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-307d8179 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"307d8179\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes malware analysis:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-23226461 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"23226461\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI speeds up classification by identifying code similarities across malware families and generating explanations of sandbox execution. It helps analysts quickly grasp how malware works, supporting faster response and more effective mitigations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-62f12026 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"62f12026\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Response.<\/strong> Accelerates identification and containment of malware.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-65714625 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"65714625\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Recovery.<\/strong> Contributes to knowledge building for future defenses.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-742eb9 e-con-full e-flex e-con e-child\" data-id=\"742eb9\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-78a4ba6 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"78a4ba6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: AI-assisted malware disassembly<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1d945268 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"1d945268\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2025, <a href=\"https:\/\/doi.org\/10.48550\/arXiv.2504.07574\">Apvrille and Nakov<\/a> evaluated R2AI, an AI plugin for the Radare2 disassembler, on recent Linux and IoT malware samples. The system integrates LLMs into the reverse engineering process, helping analysts decompile functions, rename variables and identify suspicious behaviours. Their study showed that AI assistance could cut analysis time from several days to roughly half, while maintaining equal or better quality than human-only analysis. For example, in the case of the Linux\/Devura malware, the AI correctly inferred argument formats that human analysts had missed. However, limitations remained: the models occasionally produced hallucinations, exaggerations, or omissions, and required constant validation by skilled experts. The findings suggest that AI-assisted disassembly is most effective as a force multiplier, accelerating triage and uncovering details more quickly, while still relying on human oversight to ensure accuracy and avoid misinterpretation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-671714c e-con-full e-flex e-con e-child\" data-id=\"671714c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ea4d306 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"ea4d306\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"ea4d306\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-ea4d306\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-ada8024 e-con-full e-flex e-con e-child\" data-id=\"ada8024\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-ea4d306\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-7674b26 e-con-full e-flex e-con e-child\" data-id=\"7674b26\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c2abbc3 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"c2abbc3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Semantic segmentation for classification - <a href=\"https:\/\/doi.org\/10.32604\/cmes.2025.061080\">\"Deep Learning with Semantic Segmentation for Malware Classification\" (Chen et al. 2025)<\/a><br> The study demonstrates that applying AI to selected parts of malware files, rather than entire file sequences, can significantly improve performance. By focusing on the header data of Portable Executable files, their model achieved 99.54% accuracy in classifying malware families. This suggests that targeting the most informative code sections enables faster and more reliable threat detection.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Few-shot learning for novel malware - <a href=\"https:\/\/doi.org\/10.1016\/j.cose.2022.102887\">\"A few-shot malware classification approach for unknown family recognition using malware feature visualization\" (Conti et al. 2022)<\/a><br> The paper proposes using few-shot learning to classify malware families with only a handful of examples, avoiding the need to re-train models whenever new malware emerges. By visualizing malware binaries as 3-channel images and testing two architectures (CSNN and Shallow-FS), the study shows high accuracy in both traditional and novel malware classification. This demonstrates the potential of few-shot approaches to improve adaptability and speed in detecting emerging threats.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-34802743011\" role=\"tabpanel\" aria-labelledby=\"training-labs\" data-tab-index=\"11\" style=\"--n-tabs-title-order: 11;\" class=\" elementor-element elementor-element-2e92139e e-con-full e-flex e-con e-child\" data-id=\"2e92139e\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-7e598b54 e-con-full e-flex e-con e-child\" data-id=\"7e598b54\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5e73c74a elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"5e73c74a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Training and labs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cf75f74 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"5cf75f74\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5fe07c66 elementor-widget elementor-widget-text-editor\" data-id=\"5fe07c66\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Training and labs provide controlled environments for hands-on cybersecurity exercises and simulations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-37e6d6c2 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"37e6d6c2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI changes training and labs:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3791879d elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"3791879d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI can generate dynamic lab scenarios tailored to learner progress, create adaptive challenges of varying difficulty, and automate feedback and assessment. This supports more realistic and scalable training.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-21cc0925 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"21cc0925\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Preparedness.<\/strong> Strengthens readiness through adaptive simulations.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div data-dce-text-color=\"#E8EEFF\" class=\"elementor-element elementor-element-1fc426ad elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"1fc426ad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div><strong>Recovery.<\/strong> Incorporates real incident lessons into training.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-dce-background-color=\"#FFFFFF\" class=\"elementor-element elementor-element-200258a6 e-con-full e-flex e-con e-child\" data-id=\"200258a6\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-675846ab elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"675846ab\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Case Highlighted: AI-powered cyber ranges for adaptive training<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5f8bc9d6 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"5f8bc9d6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In 2025, <a href=\"https:\/\/doi.org\/10.1080\/19361610.2025.2518383\">Sisodiya et al<\/a>introduced an AI-powered cyber range designed to improve the realism and effectiveness of cybersecurity training. Unlike traditional static labs, the platform uses AI to adjust the difficulty of scenarios according to learner progress, inject realistic attack events, and provide automated feedback.<\/p><p>The study found that students trained in this environment achieved higher detection accuracy and reduced mitigation times compared with conventional approaches. For educators, the system makes it possible to scale exercises, personalise challenges, and incorporate lessons from real incidents into simulations.<\/p><p>Technically, the research also demonstrated that hybrid architectures, combining cloud scalability with the fidelity of physical systems, deliver more realistic and adaptive scenarios. The findings highlight how AI can transform training from fixed exercises into dynamic learning environments that better prepare students and professionals for real cyber threats.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c9a1270 e-con-full e-flex e-con e-child\" data-id=\"c9a1270\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cf5fc34 elementor-widget elementor-widget-marcs-collapsible-content\" data-id=\"cf5fc34\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"marcs-collapsible-content.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"marcs-collapsible-wrapper\" data-widget-id=\"cf5fc34\" data-default-state=\"closed\" data-animation-duration=\"300\">\n\t\t\t<div class=\"marcs-collapsible-heading-wrapper\">\n\t\t\t\t<div class=\"marcs-collapsible-heading\">\n\t\t\t\t\tFurther readings\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle\" role=\"button\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"marcs-collapsible-content-cf5fc34\">\n\t\t\t\t\t\t<span class=\"marcs-collapsible-toggle-icon\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-closed\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t<span class=\"marcs-collapsible-icon-opened\"><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<!-- First nested container: Content Area -->\n\t\t\t<div class=\"marcs-collapsible-content-area elementor-element elementor-element-b643416 e-con-full e-flex e-con e-child\" data-id=\"b643416\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\n\t\t\t<!-- Second nested container: Collapsible Content -->\n\t\t\t<div id=\"marcs-collapsible-content-cf5fc34\" class=\"marcs-collapsible-content-wrapper marcs-collapsible-hidden elementor-element elementor-element-4780fe7 e-con-full e-flex e-con e-child\" data-id=\"4780fe7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-264405a elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"264405a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Cybersecurity training methods - <a href=\"https:\/\/doi.org\/10.1016\/j.cose.2023.103585\">\"A Systematic Review of Current Cybersecurity Training Methods\" (Pr\u00fcmmer et al. 2024)<\/a><br> The paper shows that a wide range of cybersecurity training approaches, including game-based methods, improve end-user behaviour and organisational security outcomes. Results highlight the effectiveness of structured training programmes but also reveal challenges such as small sample sizes and non-experimental designs. This underscores the value of integrating AI into training and labs to scale interventions, personalise content and generate adaptive exercises that overcome the limitations of traditional methods.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-34802743012\" role=\"tabpanel\" aria-labelledby=\"e-n-tab-title-34802743012\" data-tab-index=\"12\" style=\"--n-tabs-title-order: 12;\" class=\" elementor-element elementor-element-be89b33 e-con-full e-flex e-con e-child\" data-id=\"be89b33\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-f6e41c9 e-con-full e-flex e-con e-child\" data-id=\"f6e41c9\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9199c70 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"9199c70\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Discussion Questions<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-23c903c elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"23c903c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b7b4e39 elementor-align-start elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"b7b4e39\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Which phase of the Cyber Incident Lifecycle (prevention, preparedness, response, recovery) is most likely to be transformed by AI in the future, and which phase is AI currently making the biggest difference in? Where does AI seem least effective?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Does AI shift the balance of power in cyberspace toward defenders, or does it mostly help attackers keep the upper hand?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Will open source and widely available AI tools level the playing field for small defenders, or will advanced proprietary systems still give large organisations an overwhelming advantage?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">How does AI\u2019s ability to automate detection, triage, and response change the speed and nature of defensive operations? Could this make \u201ctraditional SOC models\u201d obsolete?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Could defenders become too dependent on AI, leading to blind spots if models fail, are poisoned, or are deceived by adversarial inputs?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Who bears responsibility if AI systems miss critical threats or make flawed recommendations: developers, deploying organisations, or human analysts who rely on them?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">How should policymakers encourage responsible use of AI in defense without stifling innovation or limiting access for educators and smaller organisations?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-angle-right\" viewBox=\"0 0 256 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">As both attackers and defenders adopt AI, will cyber conflict evolve into a contest of \u201cautonomous defense vs. autonomous offense\u201d?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-34802743013\" role=\"tabpanel\" aria-labelledby=\"e-n-tab-title-34802743013\" data-tab-index=\"13\" style=\"--n-tabs-title-order: 13;\" class=\" elementor-element elementor-element-a5f3d08 e-con-full e-flex e-con e-child\" data-id=\"a5f3d08\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-8e85a8a e-con-full e-flex e-con e-child\" data-id=\"8e85a8a\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7fac22a elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"7fac22a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Bibliography<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d3ba4e4 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"d3ba4e4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2524929 elementor-widget elementor-widget-text-editor\" data-id=\"2524929\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><a href=\"https:\/\/www.zotero.org\/google-docs\/?R4KN1l\"><span style=\"font-weight: 400;\">Alzu\u2019bi, Ahmad, Omar Darwish, Amjad Albashayreh, and Yahya Tashtoush. \u2018Cyberattack Event Logs Classification Using Deep Learning with Semantic Feature Analysis\u2019. <\/span><i><span style=\"font-weight: 400;\">Computers &amp; Security<\/span><\/i><span style=\"font-weight: 400;\"> 150 (March 2025): 104222. https:\/\/doi.org\/10.1016\/j.cose.2024.104222.\u00a0<\/span><\/a><\/p><p><a href=\"https:\/\/www.zotero.org\/google-docs\/?R4KN1l\"><span style=\"font-weight: 400;\">Ammara, Dure Adan, Jianguo Ding, and Kurt Tutschku. \u2018Synthetic Network Traffic Data Generation: A Comparative Study\u2019. arXiv:2410.16326. Version 2. Preprint, arXiv, 22 February 2025. https:\/\/doi.org\/10.48550\/arXiv.2410.16326.\u00a0<\/span><\/a><\/p><p><a href=\"https:\/\/www.zotero.org\/google-docs\/?R4KN1l\"><span style=\"font-weight: 400;\">Balasubramanian, Prasasthy, Justin Seby, and Panos Kostakos. \u2018CYGENT: A Cybersecurity Conversational Agent with Log Summarization Powered by GPT-3\u2019. arXiv:2403.17160. Preprint, arXiv, 25 March 2024. https:\/\/doi.org\/10.48550\/arXiv.2403.17160.\u00a0<\/span><\/a><\/p><p><a href=\"https:\/\/www.zotero.org\/google-docs\/?R4KN1l\"><span style=\"font-weight: 400;\">Coppolino, Luigi, Antonio Iannaccone, Roberto Nardone, and Alfredo Petruolo. \u2018Asset Discovery in Critical Infrastructures: An LLM-Based Approach\u2019. <\/span><i><span style=\"font-weight: 400;\">Electronics<\/span><\/i><span style=\"font-weight: 400;\"> 14, no. 16 (2025): 3267. https:\/\/doi.org\/10.3390\/electronics14163267.\u00a0<\/span><\/a><\/p><p><a href=\"https:\/\/www.zotero.org\/google-docs\/?R4KN1l\"><span style=\"font-weight: 400;\">Gao, Peng, Xiaoyuan Liu, Edward Choi, Sibo Ma, Xinyu Yang, and Dawn Song. \u2018ThreatKG: An AI-Powered System for Automated Open-Source Cyber Threat Intelligence Gathering and Management\u2019. arXiv:2212.10388. 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