Security Automation

This module explores security automation, focusing on the use of technology to perform security tasks automatically, reducing the need for human intervention. It covers the implementation of automated tools for threat detection, incident response, and compliance monitoring, as well as the integration of AI and machine learning to enhance these processes.

Portal > Artificial Intelligence > Security Automation

Curriculum Builder

Murphy, Kevin P. Machine Learning: A Probabilistic Perspective. Adaptive Computation and Machine Learning Series. Cambridge, Mass.: The MIT Press, 2012.

Kelleher, John D., Brian Mac Namee, and Aoife D’Arcy. Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies. 2nd ed. Cambridge, Massachusetts: The MIT Press, 2020.

Solanas, Agusti, and Antoni Martínez-Ballesté. Advances in Artificial Intelligence for Privacy Protection and Security. Vol. 1. Intelligent Information Systems. WORLD SCIENTIFIC, 2009.

https://doi.org/10.1142/6707

Han, Jiawei, Micheline Kamber, and Jian Pei. Data Mining: Concepts and Techniques. 3rd ed. Waltham, MA: Morgan Kaufmann Publishers, 2012.

Witten, Ian H., Frank Eibe, and Mark A. Hall. Data Mining: Practical Machine Learning Tools and Techniques. 3rd ed. The Morgan Kaufmann Series in Data Management Systems. Burlington, MA: Morgan Kaufmann Publishers, 2011.

Gendreau, Michel, and Jean-Yves Potvin, eds. Handbook of Metaheuristics. 2nd ed. International Series in Operations Research & Management Science 1460. New York: Springer, 2010.

Brownlee, Jason. Clever Algorithms: Nature-Inspired Programming Recipes. Revision 2. s.l.: LuLu.com, 2012.

Zhang, David, Guangming Lu, and Lei Zhang. Advanced Biometrics. 1st ed. Cham: Springer International Publishing, 2018.

https://doi.org/10.1007/978-3-319-61545-5

Jain, Anil K., Arun A. Ross, and Karthik Nandakumar. Introduction to Biometrics. New York, NY: Springer, 2011.

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Murphy, Kevin P. Machine Learning: A Probabilistic Perspective. Adaptive Computation and Machine Learning Series. Cambridge, Mass.: The MIT Press, 2012.

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