Protection against Adversarial Attacks on Malware Detectors Using Machine Learning Algorithms

— The resistance of machine learning models, applied in malware detection tools, against adversarial attacks was analyzed. An adversarial attack on these tools was developed and a method to increase resistance of malware detection tools, based on using convolutional neural networks for representatio...

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Bibliographic Details
Published in:Automatic control and computer sciences 2021-12, Vol.55 (8), p.1025-1028
Main Authors: Marshev, I. I., Zhukovskii, E. V., Aleksandrova, E. B.
Format: Article
Language:English
Subjects:
Algorithms
Artificial neural networks
Computer Science
Control Structures and Microprogramming
Machine learning
Malware
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Description
Summary:— The resistance of machine learning models, applied in malware detection tools, against adversarial attacks was analyzed. An adversarial attack on these tools was developed and a method to increase resistance of malware detection tools, based on using convolutional neural networks for representation of assembler code of the program, was proposed.
ISSN:0146-4116
1558-108X
DOI:10.3103/S0146411621080198