Detecting Binary Perturbation Using Advanced Machine Learning Techniques
Bamidele Ajayi
Traditional malware defences based on signature matching are increasingly ineffective against polymorphic and metamorphic variants, which easily evade exact-match detection. The research community now uses machine learning models to extract behavioural and structural patterns from both static and dynamic attributes in...
- University of Sunderland
- DOI: 10.67645/pxka6712