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.

Robust Malware Classification via Deep Graph Networks on Call Graph Topologies

Mercaldo F.;
2021-01-01

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/128103
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