A comprehensive survey published on arXiv reviews the application of artificial intelligence (AI) in security alert screening and alert fatigue mitigation within Security Operations Centers (SOCs) from 2015 to 2026 1.

The survey, titled "AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey," synthesizes 119 records, including 87 core studies 1.

The research, authored by Samuel Ndichu and five other researchers, examines how AI can improve the efficiency and effectiveness of SOCs 1.

The survey organizes the AI-driven alert screening process into a four-stage workflow taxonomy: filtering, triage, correlation, and generative augmentation 1.

The study identifies gaps in the current implementation of AI in SOCs, specifically in deployment realism, adversarial robustness, cross-environment validation, and evaluation practices 1.

The authors conclude with a research agenda focused on establishing trustworthy Cognitive Security Operations Centers 1.

The survey's abstract highlights the importance of security alert screening as a critical task within SOCs, involving filtering, prioritizing, correlating, and contextualizing alerts for analysts 1.

The paper is 35 pages long and includes 5 figures and 9 tables. Supplementary materials are also available 1.

The survey was submitted to ACM Computing Surveys 1.

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