Title: Research on the application of network intrusion feature extraction in power network

Authors: Li Yichao; Zhang Lei; Yi Jinci; Wang Jun

Addresses: State Grid Hebei Information and Communications Technology Company, Shijiazhuang, 050022, China ' State Grid Hebei Information and Communications Technology Company, Shijiazhuang, 050022, China ' State Grid Hebei Information and Communications Technology Company, Shijiazhuang, 050022, China ' State Grid Hebei Information and Communications Technology Company, Shijiazhuang, 050022, China

Abstract: In order to overcome the problems of low accuracy and high time cost of traditional methods of power grid intrusion feature extraction, a method of power grid intrusion feature extraction based on fuzzy c-means clustering is proposed, and a power statistical sequence model is established. The structure of intrusion statistical feature sequence is reconstructed by using fuzzy association rule scheduling method. Extract the spectrum density feature of power grid intrusion sequence, realise the optimal clustering processing of Power Grid Intrusion Feature by fuzzy c-means clustering method, and realise the automatic clustering processing of Power Grid Intrusion Feature by global optimisation method. The experimental results show that this method can achieve the automatic clustering of intrusion feature extraction and improve the anti attack ability of power grid.

Keywords: network intrusion; feature extraction; power network; detection; fuzzy c-means clustering; power grid intrusion feature.

DOI: 10.1504/IJAACS.2021.119120

International Journal of Autonomous and Adaptive Communications Systems, 2021 Vol.14 No.4, pp.342 - 353

Received: 10 Sep 2019
Accepted: 26 Mar 2020
Published online: 23 Nov 2021 *

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