Object

Title: Оbfuscated Мalware Detection Model

Publication Details:

This issue of the Periodical is dedicated to the 85-th anniversary of Hrant B. Marandjian, Doctor of Physical and Mathematical Sciences, Professor, Corresponding Member of NAS RA, Academician of the Russian Academy of Natural Sciences.

Journal or Publication Title:

Математические вопросы кибернетики и вычислительной техники=Կիբեռնետիկայի և հաշվողական տեխնիկայի մաթեմատիկական հարցեր=Mathematical problems of computer science

Date of publication:

2024

Volume:

62

ISSN:

2579-2784 ; e-2538-2788

Additional Information:

click here to follow the link

Coverage:

72-81

Abstract:

The paper presents the research results on the detection of obfuscated malware using a method based on mean shift. The research aimed to train neural networks included in the intrusion detection system to detect obfuscated malware. Detection of obfuscated malware using deterministic obfuscators is also discussed. Software solutions Dotfuscator CE, Net Reactor, and Pro Guardwere used as deterministic obfuscators. Athena, abc, cheeba, dyre, december_3, engrat, surtr, stasi, otario, dm, v-sign, tequila, flip, grum, mimikatz were used as test malware. The results were verified using the IDA Pro tool and various intrusion detection systems. Process modeling was carried out in the Hyper-V virtual environment.

Publisher:

Изд-во НАН РА

Format:

pdf

Identifier:

oai:arar.sci.am:406427

Location of original object:

ՀՀ ԳԱԱ Հիմնարար գիտական գրադարան

Object collections:

Last modified:

Aug 19, 2025

In our library since:

Aug 19, 2025

Number of object content hits:

2

All available object's versions:

https://arar.sci.am/publication/438985

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