AGENTIC AI AND CYBER SECURITY: AUTONOMOUS THREAT HUNTING, INTRUSION DETECTION, AND ADAPTIVE DEFENSE MECHANISMS IN A WORLD OF INCREASINGLY SOPHISTICATED CYBER ATTACKS

Abstract

This study investigates the transformative potential of agentic artificial intelligence (AI) systems in enhancing cybersecurity through autonomous threat hunting, real-time intrusion detection, and adaptive defense mechanisms. Employing a mixed-methods research design, the investigation analyzes a large-scale dataset comprising 2.4 million network events collected from January 2023 to December 2024 across 150 enterprise environments. A custom agentic AI framework built on reinforcement learning

Categories

@article{rangappa2026agentic,
  title = {{AGENTIC AI AND CYBER SECURITY: AUTONOMOUS THREAT HUNTING, INTRUSION DETECTION, AND ADAPTIVE DEFENSE MECHANISMS IN A WORLD OF INCREASINGLY SOPHISTICATED CYBER ATTACKS}},
  author = {Ajay Simha Rangappa},
  year = {2026},
  month = mar,
  journal = {Journal of Digital Security and Forensics},
  doi = {10.29121/digisecforensics.v2.i1.2025.86},
  url = {https://www.semanticscholar.org/paper/341d785475da2663203fc3ccaa1bca71968310bb}
}