Abstract
With the continuous improvement of the automation level of the electric energy metering system, the measurement security threats it facing increased contrast. Aiming at the fuzzy and dynamic characteristics of the information safety grade of the electric energy metering system, a multi-level and multi-factor security comprehensive evaluation model based on dynamic fuzzy theory which proposes a safety classification evaluation method based on dynamic double fuzzy reasoning, was established based on the study of the security static evaluation model. In this paper, the information security evaluation index system is established by analyzing the related factors of confidentiality, integrity and availability of electric energy measurement information security. The dynamic fuzzy probability vector of the safety grade is calculated based on the ameliorated D-S evidential theory, then the static weight determined by FAHP based on triangular fuzzy number and the time weight determined by the information entropy weight method based on time degree are integrated to calculate the dynamic weight vector of the index, and finally combines examples to analyze and verify the resulting data. This paper provided new solutions for the information security classification evaluation of the electric energy metering automation system.
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Liu, T., Wu, S., Peng, T., Li, S., Zhao, J., Cao, X. (2021). The Evaluation Method of Safety Classification for Electric Energy Measurement Based on Dynamic Double Fuzzy Reasoning. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12736. Springer, Cham. https://doi.org/10.1007/978-3-030-78609-0_21
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