AI-Driven Security: Enhancing Large Language Models and Cybersecurity

In an era of rapid advancements in artificial intelligence, cybersecurity threats continue to evolve, particularly in the domain of large language models, financial systems, and password security. This book delves into the critical aspects of AI-driven security, offering insights into risk management, defensive mechanisms, and ethical AI deployment. Through a structured approach, this book explores:1.The vulnerabilities of financial large language models and prompt injection attack defenses.2.Ownership protection mechanisms through watermarking and fingerprinting techniques.3.AI-powered security policy automation for operating systems.4.Password security analysis leveraging hybrid rule-based and ML techniques. With extensive research and case studies, "AI-Driven Security" provides a comprehensive guide to fortifying AI applications against cyber threats, making it a must-read for cybersecurity professionals, AI researchers, and industry practitioners.

Autorentext
Rajesh Daruvuri is an AI and cloud leader, shaping security, business intelligence, and AI ethics. An IEEE senior member and SXSW judge, he mentors and speaks at global AI forums.Kiran Kumar Patibandla is a technologist with 20+ years of innovation, pioneering Conversational AI and AI-driven retail insights, with patents in digital media and GenAI.