Affiliations: Faculty of Information Management, Shanxi University of Finance & Economics, Taiyuan, Shanxi, China
Correspondence:
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Corresponding author. Renshang Zhang, Faculty of Information Management, Shanxi University of Finance & Economics, Taiyuan, Shanxi, China. E-mail: renshangz@126.com.
Abstract: In order to strengthen the overall security of the network, this paper analyzes the network security issues. The study of the network security is carried out based on the Prefix Span algorithm for data mining. The classical data mining algorithm, Prefix Span algorithm and its improvement are proposed. Then, combined with the characteristics of network security, the proposed algorithm is applied to network security intrusion detection. From the algorithm flow and evaluation model, an optimization and update scheme is proposed, and an effective data transmission evaluation model is established by effectively evaluating the status of data analysis. The experimental results show that the efficiency of the algorithm is higher than the original one. In the long sequence mode mining, the algorithm has more advantages and can better meet the high requirements of intrusion detection. However, due to the diversity and complexity of intrusion methods, data mining still needs deeper research and performance improvement in intrusion detection.
Keywords: Prefix span algorithm, data mining, cyber security
