1 citations · 1 across the 7 of their papers we have counts for
8 papers
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…
From One Attack Domain to Another: Contrastive Transfer Learning with Siamese Networks for APT Detection
Sidahmed Benabderrahmane, Talal Rahwan
Advanced Persistent Threats (APT) pose a major cybersecurity challenge due to their stealth, persistence, and adaptability. Traditional machine learning detectors struggle with cla…
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…
Adversarial Augmentation and Active Sampling for Robust Cyber Anomaly Detection
Sidahmed Benabderrahmane, Talal Rahwan
Advanced Persistent Threats (APTs) present a considerable challenge to cybersecurity due to their stealthy, long-duration nature. Traditional supervised learning methods typically…
Attackers Strike Back? Not Anymore -- An Ensemble of RL Defenders Awakens for APT Detection
Sidahmed Benabderrahmane, Talal Rahwan
Advanced Persistent Threats (APTs) represent a growing menace to modern digital infrastructure. Unlike traditional cyberattacks, APTs are stealthy, adaptive, and long-lasting, ofte…
Metric Matters: A Formal Evaluation of Similarity Measures in Active Learning for Cyber Threat Intelligence
Sidahmed Benabderrahmane, Talal Rahwan
Advanced Persistent Threats (APTs) pose a severe challenge to cyber defense due to their stealthy behavior and the extreme class imbalance inherent in detection datasets. To addres…