Winning the Battle for Secure ML by Bestan Maaroof (.ePUB)+
File Size: 10.9 MB
Winning the Battle for Secure ML by Bestan Maaroof
Requirements: .ePUB, .PDF reader, 10.9 MB | True PDF, True EPUB
Overview: This book provides a comprehensive yet methodical understanding of securing today’s AI systems. It covers vulnerabilities throughout the complete Machine Learning life cycle from data collection, to training, and deployment and inference, as well as presents practical methods for mitigating the most harmful threats. By integrating theoretical foundations, practical case studies, and recent research, the book covers essential topics including threat modelling, adversarial attacks, poisoning attacks, and privacy breaches. This book exclusively focused on Machine Learning Security and provides a comprehensive yet methodical understanding of securing today’s AI systems. It covers vulnerabilities throughout the complete Machine Learning life cycle from data collection, to training, and deployment and inference, as well as presents practical methods for mitigating the most harmful threats. By integrating theoretical foundations, practical case studies, and recent research, the book covers essential topics including threat modelling, adversarial attacks, poisoning attacks, and privacy breaches. To facilitate learning and usability, review questions to check understanding, and practical exercises to apply important concepts to practical situations are included in each chapter. This text, aimed at upper-level undergraduates and graduate students, along with Computer Science, cybersecurity, and AI practitioners, presumes a solid foundation in Machine Learning principles. The book provides readers with actionable, research-based information on the evolving security and privacy issues in Artificial Intelligence.
Genre: Non-Fiction > Tech & Devices
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