AI-Driven Threat Detection and Incident Response
Tarun Kumar Vashishth, Vikas Sharma, Mukesh Kumar Sharma, Rajeev Sharma, Kewal Krishan Sharma, Sangeeta V. Sharma · Advances in computational intelligence and robotics book series · 2025
The rise of sophisticated cyber threats necessitates advanced security mechanisms for real-time threat detection and incident response. This chapter explores the integration of Artificial Intelligence (AI) and Machine Learning (ML) in cybersecurity to enhance threat detection, anomaly identification, and automated incident response. It examines ML-based anomaly detection techniques, deep learning models for malware classification, and AI-driven intrusion detection systems. Additionally, it highlights the role of AI in automating Security Operations Centers (SOCs) and improving response efficiency. By leveraging AI-driven playbooks and predictive analytics, organizations can proactively mitigate cyber risks. The chapter also discusses challenges, ethical considerations, and future research directions in AI-powered cybersecurity solutions.