Generative AI for Cybersecurity explores how rapidly evolving generative models are reshaping modern digital defense. As organizations become more interconnected and data-driven, traditional cybersecurity measures are increasingly challenged by adaptive, AI-powered threats. Generative AI introduces new capabilities that can significantly enhance threat detection, automate security operations, and improve situational awareness, but it also enables sophisticated offensive techniques, deepfakes, automated malware generation, and large-scale misinformation.
This book provides a balanced and comprehensive examination of this dual-use technology. It highlights how generative models can be leveraged to build resilient, intelligent, and proactive defense mechanisms capable of anticipating and countering emerging cyber risks. At the same time, it critically analyzes the vulnerabilities, ethical dilemmas, and regulatory challenges introduced by the misuse of generative AI. Through diverse perspectives and expert contributions, the book bridges theoretical foundations with real-world applications, demonstrating how GenAI can support adaptive intrusion detection, anomaly analysis, secure autonomous systems, and more transparent and explainable security solutions.
Beyond technical considerations, the book addresses broader societal, geopolitical, and governance implications, including issues of trust, sovereignty, and responsible AI deployment. It offers frameworks, methodologies, and practical insights suitable for researchers, practitioners, students, and policymakers seeking to understand, develop, or regulate GenAI-driven cybersecurity systems.
By examining both the opportunities and the risks, Generative AI for Cybersecurity serves as a timely reference for navigating an era where AI is not only a tool for defense but also a catalyst for new forms of cyber aggression, highlighting the urgent need for innovative, ethical, and resilient approaches to securing the digital world.
