Proactive zero-day malware evolution forecasting via self-supervised multi-view contrastive representation learning and hybrid generative modeling
A multiple-view self-supervised malware evolution forecasting framework that shifts focus from merely detecting malware to proactively anticipating future threats, showing improved detection performance, better zero-day/out-of-distribution generalization, more realistic and behaviorally consistent generated samples, an...