Explainable AI in Intrusion Detection for Resource-Constrained Organizations: A SHAP-LLM Framework with Adversarial Robustness Evaluation
Forthcoming, under peer review
Chinemelum Umealajekwu
Forthcoming
Combines SHAP explanations with a language model to make intrusion detection decisions understandable for teams without dedicated security analysts, and evaluates how the system holds up against adversarial attacks.
A systematic review, using the PRISMA 2020 methodology, of how artificial intelligence is used for cybersecurity threat detection and response in U.S. financial institutions.
IRE Journals · Vol. 8 Iss. 6, pp. 1102–1115 · December 31, 2024
Proposes the CLOSO (Cognitive Load Optimized Security Operations) framework for how AI and human analysts can work together in a security operations center to reduce analyst workload and cognitive fatigue.