Interpretable and adversarially-resistant behavioral malware signatures
Xiao Han, Baptiste Olivier · 2020
Machine learning based techniques have been widely applied to dynamic malware analysis. However, such techniques largely complicate the understanding of predicted results due to their algorithm complexity. The situation becomes even worse with the application of deep learning techniques, which usually include complex architectures with multiple layers of transformations. In addition, most learning-based approaches are potentially vulnerable to behavior transformation attacks.