Title: A precise sensing method of campus network security situation based on fuzzy clustering algorithm

Authors: Ranran Yin; Zhenyu Yang

Addresses: Department of Urban Rail Transit and Information Engineering, Anhui Communications Vocational and Technical College, Hefei, 230051, Anhui, China ' Information Management Center, Anhui Communications Vocational and Technical College, Hefei, 230051, Anhui, China

Abstract: To ensure the safe operation of the campus network and improve the sensing accuracy and convergence speed, a precise sensing method for campus network security situations based on a fuzzy clustering algorithm is proposed. Firstly, the constructed element model is used to extract the situation elements, and the situation information is processed through the non-negative matrix decomposition algorithm. Secondly, the Kalman entropy method is used to estimate the security situation of the whole network of the network campus, and the new information on the network security situation is calculated. Finally, according to the characteristics of campus network security situation awareness, the network security situation awareness is realised through a fuzzy clustering algorithm. The experimental results show that the MAPE value and RMSE value of the proposed method are low, and the RMSE value is maintained below 0.15, the convergence speed is fast, and can comprehensively reflect the network security situation.

Keywords: fuzzy clustering algorithm; campus network; security situation awareness; Kalman filter model; transitive closure.

DOI: 10.1504/IJWBC.2025.147391

International Journal of Web Based Communities, 2025 Vol.21 No.3, pp.219 - 232

Received: 14 Jun 2023
Accepted: 10 Oct 2023
Published online: 15 Jul 2025 *

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