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Autonomous Defenders: Generative AI for Smarter Incident Response - AI-Augmented Security Operations in Modern SOCs
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Author(s): M. P. Rajakumar (St. Joseph's College of Engineering, India), M. Balasubramani (V.S.B. Engineering College. Karur, India), R. Balamurugan (New Prince Shri Bhavani College of Engineering and Technology, India), M. Navaneetha Krishnan (St.Joseph College of Engineering, India), M. Robinson Joel (KCG College of Technology, Karapakkam, India)and Joel Jacson (Kings Engineering College, India)
Copyright: 2027
Pages: 30
Source title:
Generative AI for Cyber Risk Management
Source Author(s)/Editor(s): Yassine Maleh (Sultan Moulay Slimane University, Morocco), Lahby Mohamed (Hassan II University, Casablanca, Morocco)and Ahmed A. Abd El-Latif (Prince Sultan University, Saudi Arabia)
DOI: 10.4018/979-8-3693-8397-1.ch005
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Abstract
This chapter examines the transformative role of generative artificial intelligence in modern incident response, focusing on how AI-driven models enhance detection, triage, analysis, and remediation workflows within Security Operations Centers. The chapter outlines limitations of traditional human-centered response frameworks and demonstrates how large language models, reinforcement learning agents, and multimodal generative systems provide adaptive, context-aware decision support. A conceptual architecture for autonomous defenders is introduced, illustrating how generative AI integrates with SIEM, SOAR, and XDR platforms to enable semi-autonomous and fully automated security actions. Ethical, regulatory, and governance considerations are discussed to ensure responsible deployment of AI-driven cyber defense capabilities. The chapter concludes by identifying emerging research directions and outlining future trends that will shape AI-augmented incident response ecosystems.
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