Method for Distributed Detection Malicious Activity Based on Analysis of Execution Behavior

This article explores the challenges of detecting malware that employs various evasion techniques. Key malware masking techniques are described and analysed. The impact of polymorphism techniques on the execution of low-level instructions is examined in detail. A method is presented for forming program execution behaviour. The proposed approach involves a software tool consisting of an emulator and a sandbox. An approach for forming program behaviour based on compiled states is introduced. The method involving the computer system, modified isolated environments, and analysis of program execution behaviour is demonstrated. Experiments are described, and conclusions are drawn regarding the improvement of malware detection accuracy using the proposed approach.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1109/dessert65323.2024.11122133
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
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article

Method for Distributed Detection Malicious Activity Based on Analysis of Execution Behavior

Anatoliy Sachenko, Олег Савенко, Antonina Kashtalian, Pavlo Rehida
Network Security and Intrusion Detection
article

Method for Distributed Detection Malicious Activity Based on Analysis of Execution Behavior

Anatoliy Sachenko, Олег Савенко, Antonina Kashtalian, Pavlo Rehida
article en

Abstract

This article explores the challenges of detecting malware that employs various evasion techniques. Key malware masking techniques are described and analysed. The impact of polymorphism techniques on the execution of low-level instructions is examined in detail. A method is presented for forming program execution behaviour. The proposed approach involves a software tool consisting of an emulator and a sandbox. An approach for forming program behaviour based on compiled states is introduced. The method involving the computer system, modified isolated environments, and analysis of program execution behaviour is demonstrated. Experiments are described, and conclusions are drawn regarding the improvement of malware detection accuracy using the proposed approach.

Khmelnytskyi National University (UA), Kazimierz Pułaski University of Technology and Humanities in Radom (PL)
Peace, Justice and strong institutions
Openalex Percentile: Top 63%
Network Security and Intrusion Detection
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