Robust Malware Classification via Deep Graph Networks on Call Graph Topologies

We propose a malware classification system that is shown to be robust to some common intra-procedural obfuscation techniques. Indeed, by training the Contextual Graph Markov Model on the call graph representation of a program, we classify it using only topological information, which is unaffected by such obfuscations. In particular, we show that the structure of the call graph is sufficient to achieve good accuracy on a multi-class classification benchmark.