{"product_id":"adversarial-machine-learning-by-jason-edwards-9781394402038","title":"Adversarial Machine Learning","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003cstrong\u003eEnables readers to understand the full lifecycle of adversarial machine learning (AML) and how AI models can be compromised\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003cem\u003eAdversarial Machine Learning\u003c\/em\u003e is a definitive guide to one of the most urgent challenges in artificial intelligence today: how to secure machine learning systems against adversarial threats.\u003c\/p\u003e\n\n\u003cp\u003eThis book explores the full lifecycle of adversarial machine learning (AML), providing a structured, real-world understanding of how AI models can be compromised—and what can be done about it.\u003c\/p\u003e\n\n\u003cp\u003eThe book walks readers through the different phases of the machine learning pipeline, showing how attacks emerge during training, deployment, and inference. It breaks down adversarial threats into clear categories based on attacker goals—whether to disrupt system availability, tamper with outputs, or leak private information. With clarity and technical rigour, it dissects the tools, knowledge, and access attackers need to exploit AI systems.\u003c\/p\u003e\n\n\u003cp\u003eIn addition to diagnosing threats, the book provides a robust overview of defence strategies—from adversarial training and certified defences to privacy-preserving machine learning and risk-aware system design. Each defence is discussed alongside its limitations, trade-offs, and real-world applicability.\u003c\/p\u003e\n\n\u003cp\u003eReaders will gain a comprehensive view of today’s most dangerous attack methods including:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eEvasion attacks that manipulate inputs to deceive AI predictions\u003c\/li\u003e\n  \u003cli\u003ePoisoning attacks that corrupt training data or model updates\u003c\/li\u003e\n  \u003cli\u003eBackdoor and trojan attacks that embed malicious triggers\u003c\/li\u003e\n  \u003cli\u003ePrivacy attacks that reveal sensitive data through model interaction and prompt injection\u003c\/li\u003e\n  \u003cli\u003eGenerative AI attacks that exploit the new wave of large language models\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eBlending technical depth with practical insight, \u003cem\u003eAdversarial Machine Learning\u003c\/em\u003e equips developers, security engineers, and AI decision-makers with the knowledge they need to understand the adversarial landscape and defend their systems with confidence.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":47306886840556,"sku":"9781394402038","price":236.0,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/12560023482684.jpg?v=1771065143","url":"https:\/\/bookhero.co.nz\/products\/adversarial-machine-learning-by-jason-edwards-9781394402038","provider":"Book Hero","version":"1.0","type":"link"}