A Multi-Modal Deep Learning Framework for Robust Polymorphic Malware Detection
A Hybrid Multi-Modal Deep Learning framework that combines visual and structural features reduces modality collapse and creates a much stronger system compared to using either input type on its own, improves detection performance on deeply hidden contemporary threats, including the AveMariaRAT and CobaltStrike families.