Identification of Processor’s Architecture of Executable Code Based on Machine Learning. Part 2. Identification method
Mikhail Buinevich, Израилов Константин Евгеньевич · Proceedings of Telecommunication Universities · 2020
This article shows us the study results of a method for identifying the processor architecture of an executable code based on machine learning. In the second part of the series of articles, a three-stage scheme of the method and the corresponding software are synthesized. The functional and information layer of the architecture of the tool, as well as its operation modes, are described. Basic testing of the tool is carried out and the results of its work are given. By the example of identification of files with machine code of various architectures, the efficiency of the proposed method and means is substantiated.