Adversarial Machine Learning : Mechanisms, Vulnerabilities, and Strategies for Trustworthy AI

defense strategies from adversarial training and certified defenses to privacy-preserving machine learning and risk-aware system design. Each defense is discussed alongside its limitations, trade-offs, and real-world applicability. Readers will gain a comprehensive view of today???s most dangerous attack methods including: Evasion attacks that manipulate inputs to deceive AI predictions Poisoning attacks that corrupt training data or model updates Backdoor and trojan attacks that embed malicious triggers Privacy attacks that reveal sensitive data through model interaction and prompt injection Generative AI attacks that exploit the new wave of large language modelsBlending technical depth with practical insight, Adversarial Machine Learning equips developers, security engineers, and AI decision-makers with the knowledge they need to understand the adversarial landscape and defend their systems with confidence. [Publisher's Text]

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