AUGMENTING SIEM WITH THREAT INTELLIGENCE FOR PREDICTIVE CYBER DEFENSE: A PROACTIVE THREAT HUNTING APPROACH
Abstract
Security Information and Event Management (SIEM) systems play a crucial role in detecting and responding to cyber threats through real-time monitoring and log analysis. However, traditional SIEMs often struggle with proactively identifying emerging threats. This paper explores the augmentation of SIEM platforms with external and internal Cyber Threat Intelligence (CTI) to enhance predictive cyber defense capabilities. By integrating threat intelligence feeds, behavioral analytics, and machine learning techniques, the proposed approach transforms SIEMs from reactive tools into proactive threat hunting systems. The study reviews current architectures, implementation challenges, and real-world use cases, demonstrating how enriched SIEM environments improve threat detection, reduce false positives, and support faster incident response. The paper also outlines future directions for building adaptive, intelligence-driven security operations.
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