Walter Maanyere

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...