Protection against Adversarial Attacks on Malware Detectors Using Machine Learning Algorithms

被引：1
|
作者：
Marshev, I. I. [1 ]
Zhukovskii, E., V [1 ]
Aleksandrova, E. B. [1 ]
机构：
[1] Peter Great St Petersburg Polytech Univ, St Petersburg 195251, Russia
来源：
AUTOMATIC CONTROL AND COMPUTER SCIENCES | 2021年 / 55卷 / 08期
关键词：
malware detection; machine learning; adversarial attacks; neural networks; statistical analysis;
D O I：
10.3103/S0146411621080198
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1025 / 1028
页数：4
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