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About the Book
Adversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips you with the skills to secure AI technologies, moving beyond research hype or business-as-usual activities. Learn how to defend AI and LLM systems against manipulation and intrusion through adversarial attacks such as poisoning, trojan horses, and model extraction, leveraging DevSecOps, MLOps, and other methods to secure systems.
This strategy-based book is a comprehensive guide to AI security, combining structured frameworks with practical examples to help you identify and counter adversarial attacks. Part 1 introduces the foundations of AI and adversarial attacks. Parts 2, 3, and 4 cover key attack types, showing how each is performed and how to defend against them. Part 5 presents secure-by-design AI strategies, including threat modeling, MLSecOps, and guidance aligned with OWASP and NIST. The book concludes with a blueprint for maturing enterprise AI security based on NIST pillars, addressing ethics and safety under Trustworthy AI.
By the end of this book, you’ll be able to develop, deploy, and secure AI systems against the threat of adversarial attacks effectively.
About the Author
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Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com