AI-Based Threat Hunting in Enterprise Security Operations Using Graph-Based Intrusion Detection Systems
Keywords:
AI-based Threat Hunting, Graph-Based Intrusion Detection, Enterprise Security, Machine Learning, Cybersecurity, Anomaly DetectionAbstract
The growing complexity of cyber threats has outpaced traditional intrusion detection systems (IDS), necessitating more adaptive and intelligent security mechanisms. AI-based threat hunting, particularly utilizing Graph-Based Intrusion Detection Systems (GBIDS), offers a dynamic and context-aware approach to identifying and mitigating cyber threats in enterprise security operations. By leveraging machine learning (ML), deep learning (DL), and graph-based analytics, security teams can map complex attack paths, uncover hidden anomalies, and proactively defend against cyber threats. This paper explores recent advancements in AI-driven threat detection, focusing on GBIDS, their role in enterprise cybersecurity, and their future research directions.
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