Generative AI Security: Defense, Threats by Shaila Rana (.ePUB)+
File Size: 10 MB
Generative AI Security: Defense, Threats, and Vulnerabilities by Shaila Rana, Rhonda Chicone
Requirements: .ePUB, .PDF, .MOBI reader, 10 MB | True/Retail PDF, True/Retail EPUB, MOBI
Overview: Up-to-date reference enabling readers to address the full spectrum of AI security challenges while maintaining model utility. Generative AI Security: Defense, Threats, and Vulnerabilities delivers a technical framework for securing Generative AI systems, building on established standards while focusing specifically on emerging threats to large language models and other Generative AI systems. Moving beyond treating AI security as a dual-use technology, this book provides detailed technical analysis of three critical dimensions: implementing AI-powered security tools, defending against AI-enhanced attacks, and protecting AI systems from compromise through attacks like prompt injection, model poisoning, and data extraction. The book provides concrete technical implementations supported by real-world case studies of actual AI system compromises, examining documented cases like the DeepSeek breaches, Llama vulnerabilities, and Google’s CaMeL security defenses to demonstrate attack methodologies and defense strategies while emphasizing foundational security principles that remain relevant despite technological shifts. Each chapter progresses from theoretical foundations to practical applications.
Genre: Non-Fiction > Tech & Devices
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