Quarterly journal published in SPbPU
and edited by prof. Dmitry Zegzhda
Peter the Great St. Petersburg Polytechnic University
Institute of computer sciences and technologies
information security of computer systems
Information Security Problems. Computer Systems
Published since 1999.
ISSN 2071-8217
M. A. Volkovskiy, T. D. Ovasapyan, A. S. Makarov Peter the Great St. Petersburg Polytechnic University
Annotation: The paper proposes a method for detecting malicious executable files by analyzing disassembled code. This method is based on static analysis of assembler instructions of executable files using a special neural network model, the architecture of which is also presented in this paper. In addition, through several different metrics, the effectiveness of the method has been demonstrated, showing a significant reduction of the second-order error compared to other state-of-the-art methods. The results obtained can be used as a basis for designing static malware analysis systems.
Keywords: detection of malicious software, static analysis, machine learning, deep neural networks, disassembled code analysis, transformer, BERT.
Pages 72-83