Artificial Intelligence Data and Model Security: Risks, Attacks and Defenses begins with a brief review of the history of AI and AI security and then introduces the fundamental aspects of machine learning and AI security. Two key aspects are covered: data security and modelling. It provides detailed explanations of a wide range of attacks and defense algorithms related to data security, as well as adversarial attack/defense, backdoor attack/defense, and extraction attack/defense algorithms related to model security. By providing a systematic, comprehensive, and in-depth introduction to the topic, this book help readers understand the advanced attack and defense techniques in the field of AI security.
1. AI and AI Security: An Introduction
2. Machine Learning Basics
3. AI Security Basics
4. Data Security: Attacks
5. Data Security: Defenses
6. Model Security: Adversarial Attacks
7. Model Security: Adversarial Defenses
8. Model Security: Backdoor Attacks
9. Model Security: Backdoor Defenses
10. Model Security: Extraction Attack Defense
11. Future Prospects
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