MESSALA is a new LLM framework that produces report evaluations closer to veteran SOC practitioners than prior LLM methods by combining a custom checklist with granularization guidelines and multi-perspective scoring.
arXiv preprint arXiv:2401.10036 (2024)
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A literature survey synthesizes 119 studies on AI-driven alert screening into a four-stage taxonomy of filtering, triage, correlation, and generative augmentation while identifying gaps in deployment realism and robustness.
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LLMs, You Can Evaluate It! Design of Multi-perspective Report Evaluation for Security Operation Centers
MESSALA is a new LLM framework that produces report evaluations closer to veteran SOC practitioners than prior LLM methods by combining a custom checklist with granularization guidelines and multi-perspective scoring.
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AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey
A literature survey synthesizes 119 studies on AI-driven alert screening into a four-stage taxonomy of filtering, triage, correlation, and generative augmentation while identifying gaps in deployment realism and robustness.