Cyber Security and Machine Learning (First Edition)

This is the page for my new book "Cyber Security and Machine Learning" (First Edition), In Python and PyTorch.
This book covers topics at the cross-section of Cyber Security and Machine Learning (ML). Specifically, the book covers the use of machine learning for Cyber Security, as well as cyber security issues associated with AI models and systems, such as AI vulnerabilities.
Topics include: the techniques of machine learning and deep learning as applied to cyber security-related datasets and problems, adversarial machine learning, LLM and other pre-trained model vulnerabilities and defenses, and more.

Available Chapters On-line

• Chapter 1 - Introduction to Cyber Security concepts
• Chapter 2 - Introduction to ML/DL concepts
• Chapter 3 - Modeling cyber security cases with ML techniques
• Chapter 4 - ML for intrusion detection systems
• Chapter 5 - ML for malware analysis
• Chapter 6 - ML for phishing attacks
• Chapter 7 - ML for network data attacks
• Chapter 8 - ML and cryptography
• Chapter 9 - Adversarial Machine Learning
• Chapter 10 - Transfer Learning vulnerabilities
• Chapter 11 - Large language models and Cyber security
• Chapter 12 - Prompt and token injection attacks
• Chapter 13 - Bias in ML
• Chapter 14 - AI Auditing
• Chapter 15 - The Alignment Problem
• Chapter 16 - AI/ML/DL evaluation, security, performance assessment
• Chapter 17 - Conclusion

Copyright, License, FTC and Amazon Disclaimer

Copyright © by Ricardo A. Calix.
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