Belal Al-sellami

Hybrid rank fusion of a group-token transformer with gradient boosting improves detection of evasive and novel-family malware

Static machine-learning malware detectors report near-perfect closed-set accuracy, but the malware that matters operationally is the malware that slips past detection and the malware that belongs to families never seen in training. We study both on three longitudinal benchmarks:...

Multistage advanced persistent threat detection and malware attribution using Mamba state space models with Kolmogorov Arnold networks

Advanced Persistent Threats (APTs) represent the most sophisticated class of cyberattacks, characterized by multi-stage, stealthy, and persistent intrusion campaigns orchestrated by well-funded, often state-sponsored adversaries. Existing detection methods suffer from three criti...