Robust Malware Classification via Deep Graph Networks on Call Graph Topologies
Federico Errica, Giacomo Iadarola, Fabio Martinelli, Francesco Mercaldo, Alessio Micheli · ESANN 2021 proceedings · 2021
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.