Power Data Security Risk Assessment Method Based on Probabilistic Hesitant Fuzzy Multi-Attribute Decision Making
Open Access
- 7 June 2024
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 65-70
Abstract
Quantitative assessment of data risks is a focal point in the field of data security. In this paper, we establish a multi-level power data security risk indicator system based on Data Security Capability Maturity Mode (DSMM) to delineate risk indicators covering the entire data lifecycle. We propose a method for representing expert evaluation information based on probabilistic hesitant fuzzy sets to mitigate issues arising from individual expert biases and the number of experts. By transforming the quantification of power data risks into a multi-attribute decision-making problem, we present a method for power data risk assessment based on probabilistic hesitant fuzzy multi-attribute group decision-making. Experimental results demonstrate that the proposed approach can effectively calculate power data risk levels, providing theoretical support for power data security protection.Keywords
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