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Found 2 papers, 2 papers with code
How to Train your Antivirus: RL-based Hardening through the Problem-Space
It also makes possible to provide theoretical guarantees on the robustness of the model against a particular set of adversarial capabilities.
Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance
As a consequence, our community still lacks an understanding of malware classification results: whether they are tied to the nature and distribution of the collected dataset, to what extent the number of families and samples in the training dataset influence performance, and how well static and dynamic features complement each other.
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