Power Distribution Internet of Things Security Risk Evaluation Based on Combined Weighting and Cloud Model

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Authors: Li Peng, Jiahai Tu, Siyuan Cai, Deng Chen
Cited by: 1
References: 16

Abstract

With the interconnection and intercommunication of Internet of Things (IoT) devices, the security risks of Power Distribution Internet of Things (PDIoT) systems have increased accordingly. How to monitor and assess these risks has become a key issue for advancing the construction and implementation of PDIoT. The traditional security evaluation methods mostly adopt a single weighting method and membership function, which are highly susceptible to subjective factors and have the characteristics of fuzziness and uncertainty. To address the problems, this paper proposes a security risk evaluation method of the PDIoT based on a combined weighting and cloud model. We first analyze the factors of security risks in PDIoT systems. A security evaluation index system for PDIoT was established based on factors from three aspects: the perception layer, network layer, and application layer, including 3 first-level indicators and 16 second-level indicators. Then, the analytic hierarchy process (AHP) and entropy weight method (EWM) are adopted for combined weighting to optimize the weight of each index; the cloud model is employed to calculate the standard evaluation and the comprehensive evaluation cloud. Subsequently, validity verification and cloud similarity calculation are performed to get the security state of the PDIoT. Finally the security evaluation level of the PDIoT system is obtained. An empirical test was conducted by taking the PDIoT of Meizhou Power Supply Bureau of Guangdong Power Grid as an example. The experimental results show that our method has better result distinguishability than the other three classical methods, allowing risk levels to be identified more clearly and intuitively.

Fields of Study & Subjects

Smart Grid Security and Resilience Technology and Security Systems IoT and Edge/Fog Computing

Publication details

Journal / source
Entropy
Publisher
MDPI AG
Volume
28
Issue
4
Pages
433–433
Publication date
12 April 2026
Language
EN