Adversarial AI Threat Response and Secure Model Design: Practical Techniques for Detecting, Preventing, and Managing AI Vulnerabilities

As artificial intelligence becomes embedded in everything from healthcare diagnostics to financial systems and autonomous vehicles, the stakes for AI security have never been higher.Adversarial AI Threat Response and Secure Model Design is your essential guide to understanding, defending against, and designing resilient machine learning systems in the face of growing adversarial threats. Written by a leading expert in AI security and policy, this book delivers a combination of technical depth, practical implementation, and strategic insight.It begins by mapping the full landscape of adversarial threats-evasion, poisoning, model extraction, backdoors, and more-across diverse data modalities and real-world applications.From there, it equips readers with a robust toolkit of detection and defense techniques, including adversarial training, anomaly detection, and formal robustness certification. But this book goes beyond code. It explores the organizational, ethical, and regulatory dimensio