WCSE

Research on Network Security Situational Awareness Based on Convolutional Neural Network

Abstract— With the continuous development of information technology, networks are becoming larger and larger, and network security is also being severely tested. At present, traditional measures to cope with network security problems, such as installing intrusion detection systems, antivirus software and firewall systems, can protect existing network security problems, but cannot predict upcoming security problems. In response to this problem, this paper optimizes the situational awareness and prediction method based on convolutional neural network. Based on experiments with the KDDCup-99 dataset, and a comparison with traditional prediction methods, the accuracy of the prediction results is verified and the network security prediction problem is effectively solved.

Index Terms—network security, situation prediction, situation assessment, convolutional neural network

Jiashuai Hu
School of Computer Science, China West Normal University, Nanchong, CHINA
Chaobin Wang
Educational Information Technology Center, China West Normal University, Nanchong, CHINA
Zifei Xiao
School of Computer Science, China West Normal University, Nanchong, CHINA
Linfeng Wu
School of Electronic Information Engineering, China West Normal University, Nanchong, CHINA

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Cite:Jiashuai Hu, Chaobin Wang, Zifei Xiao, Linfeng Wu, "Research on Network Security Situational Awareness Based on Convolutional Neural Network, " Proceedings of 2022 the 12th International Workshop on Computer Science and Engineering (WCSE 2022), pp. 313-319, June 24-27, 2022.