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GenAI-Driven Agentic Cyber Defense: An Adaptive Fabric Framework for Cross-Layer Anomaly Detection and Autonomous Enforcement
Conference proceeding   Peer reviewed

GenAI-Driven Agentic Cyber Defense: An Adaptive Fabric Framework for Cross-Layer Anomaly Detection and Autonomous Enforcement

Srikumeran Parameswaran, Bilash Saha, Kamrul Islam Riad, Muhammad Asadur Rahman and Hossain Shahriar
Proceedings : annual International Computer Software and Applications Conference, pp.2569-2574
Annual Computers, Software, and Applications Conference (COMPSAC), 50th (Madrid, Spain, 07/07/2026–07/10/2026)
08/2026
DOI: https://doi.org/10.1109/COMPSAC69091.2026.00384

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Abstract

Anomaly detection crosslayer signals GenAI Artificial Intelligence or Cybernetics Cybersecurity Telemetry Migration
Modern cyber threats are increasingly multilayered, propagating from identity compromises to network-level anomalies. Traditional SOC tools often fail to detect correlated events across domains. This research presents a GenAI-inspired Agentic AI framework integrating user behavioral analytics and network fabric telemetry into a unified anomaly detection and mitigation system. Using PCA and SVM for dimensionality reduction and classification, this framework autonomously detects anomalies, correlates cross-layer signals, and applies mitigation policies. The system demonstrates improved detection, proactive enforcement, and visual analytics support for forensic analysis.

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