Malware behavior detection method based on reinforcement learning

Jiajia Cui; Biao Leng; Xianggen Wang; Fuxi Wang; Jun Yang

doi:10.1117/12.2671736

21 March 2023 Malware behavior detection method based on reinforcement learning

Jiajia Cui, Biao Leng, Xianggen Wang, Fuxi Wang, Jun Yang

Proceedings Volume 12609, International Conference on Computer Application and Information Security (ICCAIS 2022); 126091D (2023) https://doi.org/10.1117/12.2671736
Event: International Conference on Computer Application and Information Security (ICCAIS 2022), 2022, ONLINE, ONLINE

Abstract

Malware in the network environment is a serious threat to the security of industrial control systems. With the gradual increase of malware variants, it brings great challenges to the detection and security protection of industrial control system malware. The existing detection methods have limitations such as low intelligence in adaptive detection and recognition. In response to this problem, this paper designs a detection application method framework by combining the use of reinforcement learning, an advanced machine learning algorithm, around the malware objects that threaten the network security of industrial control systems. In the implementation process, according to the actual needs of malware behavior detection, fully combined with intelligent features such as sequential decision-making and dynamic feedback learning of reinforcement learning, the key application modules such as feature extraction network, policy network and classification network are discussed and designed in detail. The application experiments based on the actual malware test data set verify the effectiveness of the method in this paper, which can provide an intelligent decision-making aid for general malware behavior detection.

Citation Download Citation

Jiajia Cui, Biao Leng, Xianggen Wang, Fuxi Wang, and Jun Yang "Malware behavior detection method based on reinforcement learning", Proc. SPIE 12609, International Conference on Computer Application and Information Security (ICCAIS 2022), 126091D (21 March 2023); https://doi.org/10.1117/12.2671736

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KEYWORDS

Machine learning

Feature extraction

Education and training

Data modeling

Network security

Control systems

Decision making

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