Malware Classification Using Static Disassembly and Machine Learning. (arXiv:2201.07649v1 [cs.CR])

Network and system security are incredibly critical issues now. Due to the
rapid proliferation of malware, traditional analysis methods struggle with
enormous samples.

In this paper, we propose four easy-to-extract and small-scale features,
including sizes and permissions of Windows PE sections, content complexity, and
import libraries, to classify malware families, and use automatic machine
learning to search for the best model and hyper-parameters for each feature and
their combinations. Compared with detailed behavior-related features like API
sequences, proposed features provide …

arxiv classification learning machine machine learning