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

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.

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Publication Details

Journal
Entropy
Published
2026-04-12
DOI
https://doi.org/10.3390/e28040433
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Deng Chen, Li Peng, Siyuan Cai, Jiahai Tu
Entropy
Smart Grid Security and Resilience
article

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

Deng Chen, Li Peng, Siyuan Cai, Jiahai Tu
article en

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.

EntropyVol. 28(4)
Hong Kong Metropolitan University (HK), Wuhan Institute of Technology (CN)
Hubei Provincial Department of Education
Openalex Percentile: Top 24%
Smart Grid Security and Resilience
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