Research on the application of network intrusion feature extraction in power network Online publication date: Tue, 23-Nov-2021
by Li Yichao; Zhang Lei; Yi Jinci; Wang Jun
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 14, No. 4, 2021
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.
Online publication date: Tue, 23-Nov-2021
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Autonomous and Adaptive Communications Systems (IJAACS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org