This book explores in detail the AI-driven cyber threat landscape, including inherent AI threats and risks that exist in Large Language Models (LLMs), Generative AI applications, and the AI infrastructure. The book highlights hands-on technical approaches to detect security flaws in AI systems and applications utilizing the intelligence gathered from real-world case studies. Lastly, the book presents a very detailed discussion of the defense mechanisms and practical solutions to secure LLMs, GenAI applications, and the AI infrastructure. The chapters are structured with a granular framework, starting with AI concepts, followed by practical assessment techniques based on real-world intelligence, and concluding with required security defenses. Artificial Intelligence (AI) and cybersecurity are deeply intertwined and increasingly essential to modern digital defense strategies. The book is a comprehensive resource for IT professionals, business leaders, and cybersecurity experts for understanding and defending against AI-driven cyberattacks.

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Aditya K. Sood (PhD) is a cybersecurity practitioner with more than 16 years of experience working with cross-functional teams, management, and customers to create the best-of-breed information security experience. His articles have appeared in magazines and journals, including IEEE, Elsevier, ISACA, Virus Bulletin, and USENIX, and he is the author of Empirical Cloud Security 2/E (Mercury Learning) and Targeted Cyber Attacks (Syngress). He has presented his research at industry leading security conferences such as Black Hat, RSA, APWG, DEFCON, Virus Bulletin, and others.

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