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Palvine Ngob Enow

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Open access Sep 2026

A PRIVACY-PRESERVING FRAMEWORK FOR INSIDER THREAT DETECTION USING PROCESS MINING, MACHINE LEARNING, AND DIFFERENTIAL PRIVACY

Insider threats remain one of the most damaging and difficult-to-detect cybersecurity risks, as malicious actors already possess legitimate access privileges. This paper presents a privacy-preserving detection framework that combines per-user process mining with differential privacy, rigorously evaluated on the officia...

Walter Maanyere, Xian-Wen Fang, Palvine Ngob Enow et al. · 0 citations

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