Malware Analysis with Symbolic Execution and Graph Kernel. (arXiv:2204.05632v1 [cs.CR])

Malware analysis techniques are divided into static and dynamic analysis.
Both techniques can be bypassed by circumvention techniques such as
obfuscation. In a series of works, the authors have promoted the use of
symbolic executions combined with machine learning to avoid such traps. Most of
those works rely on natural graph-based representations that can then be
plugged into graph-based learning algorithms such as Gspan. There are two main
problems with this approach. The first one is in the cost of …

analysis kernel malware malware analysis symbolic execution