MALWARE OBFUSCATION MODEL USING MACHINE LEARNING
Timur V. Jamgharyan, Artak Khemchyan · BULLETIN OF HIGH TECHNOLOGY · 2024
The paper presents the results of a research of the use of a generative-adversarial network for software obfuscation. The comparison was carried out with deterministic obfuscators Dotfuscator CE, Net Reactor, ProGuard. The research of changes in the source code of the software athena, abc, cheeba, dyre, december_3, engrat, surtr, stasi, otario, dm, v-sign, tequila, flip, grum, mimikatz was carried out using the IDA Pro disassembly tool. Detection of obfuscated malware was carried out based on the piecewise context fuzzy hashing method. The research was conducted to use of a generative-adversarial network as an obfuscator on pre-specified datasets. Simulation of the developed method was carried out in the Hyper-V virtual environment.