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cs.LG2026
A Source Domain is All You Need: Source-Only Cross-OS Transfer Learning for APT Anomaly Detection via Semantic Alignment and Optimal Transport
Sidahmed Benabderrahmanea, Petko Valtchev, James Cheney +1
Advanced Persistent Threats (APTs) are stealthy, multi-stage cyberattacks whose detection is difficult due to scarce labeled traces, severe class imbalance, and the challenge of ge…
cs.LG2026
Refining Decision Boundaries In Anomaly Detection Using Similarity Search Within the Feature Space
Sidahmed Benabderrahmane, Petko Valtchev, James Cheney +1
Detecting rare and diverse anomalies in highly imbalanced datasets-such as Advanced Persistent Threats (APTs) in cybersecurity-remains a fundamental challenge for machine learning…
cs.LG2025
Ranking-Enhanced Anomaly Detection Using Active Learning-Assisted Attention Adversarial Dual AutoEncoders
Sidahmed Benabderrahmane, James Cheney, Talal Rahwan
Advanced Persistent Threats (APTs) pose a significant challenge in cybersecurity due to their stealthy and long-term nature. Modern supervised learning methods require extensive la…