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Adversarial AI: Attacks & Offensive Strategies with Foolbox
Adversarial Attacks, Defenses, and Offensive Strategies with Foolbox is an in-depth guide to understanding the complex world of adversarial attacks in artificial intelligence. This book explores the vulnerabilities in AI systems, specifically machine learning models, and introduces readers to a wide array of attack techniques that can compromise their security.
Using Foolbox, a powerful library for adversarial machine learning, this book offers a comprehensive approach to implementing and evaluating 40+ different attack strategies. From gradient-based methods to more sophisticated techniques, readers will gain hands-on experience with real-world adversarial attacks and the challenges involved in securing AI systems.
Key topics
An introduction to adversarial attacks and their importance in AI security.In-depth exploration of 40+ types of adversarial attacks using Foolbox.Effective defenses against adversarial attacks and strategies to enhance model robustness.Offensive security techniques for AI systems.Whether you're a cybersecurity professional, AI researcher, or machine learning enthusiast, this book provides both theoretical knowledge and practical code examples to help you understand and secure AI systems. Explore the dark side of AI and learn how to defend your models against the growing threat of adversarial attacks.
This book is a must-have for anyone interested in the intersection of artificial intelligence, cybersecurity, and adversarial robustness.
Using Foolbox, a powerful library for adversarial machine learning, this book offers a comprehensive approach to implementing and evaluating 40+ different attack strategies. From gradient-based methods to more sophisticated techniques, readers will gain hands-on experience with real-world adversarial attacks and the challenges involved in securing AI systems.
Key topics
An introduction to adversarial attacks and their importance in AI security.In-depth exploration of 40+ types of adversarial attacks using Foolbox.Effective defenses against adversarial attacks and strategies to enhance model robustness.Offensive security techniques for AI systems.Whether you're a cybersecurity professional, AI researcher, or machine learning enthusiast, this book provides both theoretical knowledge and practical code examples to help you understand and secure AI systems. Explore the dark side of AI and learn how to defend your models against the growing threat of adversarial attacks.
This book is a must-have for anyone interested in the intersection of artificial intelligence, cybersecurity, and adversarial robustness.
352 pages, Kindle Edition
Published January 30, 2025
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