Generative AI Security

Generative AI Security: Defense, Threats, and Vulnerabilities, 1st Edition, presents a technical framework designed to secure generative AI systems. Written by Shaila Rana and Rhonda Chicone and published by Wiley-IEEE Press, this reference work addresses emerging threats targeting large language models and related enterprise technologies.

The volume divides its analytical coverage into three core areas: deploying AI-driven security utilities, repelling AI-assisted intrusion tactics, and shielding artificial intelligence infrastructure against compromise. Core coverage includes baseline machine learning methods, spanning supervised, unsupervised, and reinforcement learning alongside feature selection techniques. Additionally, the material addresses synthetic media threats, examining image and video tampering, synthetic voice cloning, audio deepfakes, and information integrity.

Hands-on exercises and an implementation guide assist readers with architecture vulnerabilities, security controls, and compliance frameworks. Every section moves systematically from foundational theory to practical application. This publication supports cybersecurity professionals, architects, engineers, IT staff, and organizational leaders seeking structured technical reference material.