Artificial Intelligence for Cybersecurity and Intrusion Detection. Lecture Notes and Solved Exercises

Bibliographic information

Publication date

2026-10-10

Pays de publication

Algérie

Edition

1re édition SARAHMED, 2026

Language

Anglais

ISBN

978-9969-17-045-0

Pages

140

Format

16 × 24 cm

Legal deposit date

2026-10-28

Classification THEMA

UTN — Sécurité réseau

Subject Area

Mathématiques et Informatique

Abstract

This textbook introduces artificial intelligence methods used in cybersecurity, with a particular focus on intrusion detection. It begins with cyberattack categories and the principles of machine learning and deep learning, then explains the preparation of network-security datasets, classifier evaluation, and the design of intrusion detection systems. Subsequent chapters examine convolutional and recurrent neural networks, autoencoders, practical model selection, explainable artificial intelligence, and federated learning for distributed detection. A smart-grid case study connects these methods to cyber-physical security, including false data injection attacks and the constraints of operational deployment. The final chapter introduces Transformers, graph neural networks, self-supervised learning, foundation models, and agentic AI in security applications. Designed as lecture notes, the book combines conceptual explanations with worked examples, graded exercises, detailed solutions, and Python code in an appendix.

Authors and contributors

Suggested citation

Sarra ARAAR. Artificial Intelligence for Cybersecurity and Intrusion Detection. Lecture Notes and Solved Exercises. SARAHMED Éditions, 2026. ISBN : 978-9969-17-045-0

Rights and licence

© 2026 Sarra ARAAR. Tous droits réservés.