Security Optimization of Convergence Nodes in the Sensing Layer of the Power Internet of Things Based on Fuzzy Clustering

Authors

  • Tong Li Beijing DualPi Intelligent Security Technology Co. Ltd, Beijing 100088, China
  • Yang Liu Beijing DualPi Intelligent Security Technology Co. Ltd, Beijing 100088, China
  • YaoDong Tao Liaoning Electric Power Research Institute, Liaoning 110055,China
  • DongHua Huang Liaoning Electric Power Research Institute, Liaoning 110055,China
  • Hongbi Geng Beijing DualPi Intelligent Security Technology Co. Ltd, Beijing 100088, China
  • Qian Sun Beijing DualPi Intelligent Security Technology Co. Ltd, Beijing 100088, China

Abstract

The use of computer networks has made daily life more convenient. However, malicious attacks and data theft by attackers with ulterior motives plague a large number of Internet users and data security is an urgent need. In this context, this article studies the security optimization of the sensory layer convergence node of the Power Internet of Things using the clustering algorithm to make it more reliable. Therefore, this paper proposes to improve the clustering algorithm through the improved type-2 fuzzy C-means clustering algorithm to explore data security, and design a simulation experiment, and through the three different attack modes of RFID system defense, the intrusion capability is compared, and the optimal type-2 fuzzy C-means clustering algorithm is obtained. The improved algorithm improves the system’s anti-intrusion success rate by 50%, which can well protect the computer network and protect user data.

Keywords: Fuzzy Clustering Algorithm, Power Internet of Things, Internet of Things Perception Layer, Convergence Node Security Optimization

Cite As

T. Li, Y. Liu, Y. Tao, D. Huang, H. Geng, Q. Sun, "Security Optimization of Convergence Nodes in the Sensing
Layer of the Power Internet of Things Based on Fuzzy Clustering", Engineering Intelligent Systems, vol. 30
no. 6, pp. 453-463, 2022.




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Published

2022-11-01

Issue

Vol. 30 No. 6 (2022): International Journal of Engineering Intelligent Systems

Section

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