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RETRACTED ARTICLE: Intrusion detection and performance simulation based on improved sequential pattern mining algorithm

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This article was retracted on 01 December 2022

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Abstract

Traditional network intrusion detection algorithm is based on pattern matching, which has made great progress in network intrusion detection system, but the efficiency of this algorithm for data packet matching is quite low. With the rapid increase of Internet scale and capacity, the general information security problem appears, and it brought hidden danger for an open network security. In this paper, the author analyse the intrusion detection and performance simulation based on improved sequential pattern mining algorithm. We integrate the data mining algorithms to implement the IDS, and the simulation result reflects the effectiveness of the methodology. The simulation shows that when minimum support is very small, PrefixSpan running time running a lot less time than other algorithm, and the difference between the two is obvious. Due to the mining algorithm of the relative independence of intrusion detection system, algorithm does not depend on the specific data and specific system, so the intrusion detection system based on data mining to data source requirement is very low.

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Acknowledgement

This paper was supported by (1) National Natural Science Foundation of China (31702232); (2) Education teaching reform project of Henan(2019-JSJYYB-056); (3) Education teaching reform project of Zhoukou normal university (J2019002).

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Correspondence to Huaibo Sun.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s10586-022-03832-8

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Wang, Y., Liang, Y., Sun, H. et al. RETRACTED ARTICLE: Intrusion detection and performance simulation based on improved sequential pattern mining algorithm. Cluster Comput 23, 1927–1936 (2020). https://doi.org/10.1007/s10586-020-03129-8

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  • DOI: https://doi.org/10.1007/s10586-020-03129-8

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