Artificial Intelligence : Data and Model Safety

Jiang, Yu-Gang/ Ma, Xingjun/ Wu, Zuxuan

Elsevier - Health Sciences Division（2025/08発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 386 p.
• 言語 ENG
• 商品コード 9780443248405
• DDC分類 006.3

Full Description

Artificial Intelligence Data and Model Safety: Risks, Attacks and Defenses offers a comprehensive overview of the evolution of AI and its security concerns. The book delves into how historical advancements in AI have both bolstered and complicated the issue of safeguarding data and models. By reflecting on the interplay between machine learning innovations and vulnerabilities, it sets the stage for readers to understand the critical importance of robust defenses in this era of digital and algorithmic reliance. In addition to contextualizing the historical trajectory of AI security, the book examines foundational elements of machine learning, emphasizing the mechanisms that contribute to, or mitigate, risks.

Readers are guided through case studies of real-world attacks, illustrating the practical implications of security weaknesses, while proposed defense strategies provide actionable insights for strengthening AI systems.

Contents

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