Open access
Aug 2026
Proactive zero-day malware evolution forecasting via self-supervised multi-view contrastive representation learning and hybrid generative modeling
Zero-day malware continues to pose a significant challenge in cybersecurity, primarily due to the rapid development of polymorphic and metamorphic variants that evade traditional detection methods based on signatures or machine learning (ML). Most existing ML approaches are reactive, identifying specific malware famili...
Abdulbasid S. Banga, Mazen Jamal, Tayyab Khan et al.
· Discover Computing · 0 citations