Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram

被引:0
|
作者
Tian, Yuechi [1 ,2 ,3 ]
Li, Fenghua [1 ,2 ,3 ]
Zhou, Zejun [1 ,2 ,3 ]
Sun, Zhe [4 ]
Guo, Shoukun [1 ,3 ]
Niu, Ben [1 ,3 ]
机构
[1] Institute of Information Engineering, Chinese Academy of Sciences, Beijing,100085, China
[2] School of Cyber Security, University of Chinese Academy of Sciences, Beijing,100049, China
[3] Key Laboratory of Cyberspace Security Defense, Beijing,100085, China
[4] Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou,510006, China
来源
关键词
Differential privacy;
D O I
10.11959/j.issn.1000-436x.2024122
中图分类号
学科分类号
摘要
In response to the challenge of comprehensively assessing privacy-preserving algorithms, an assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram was proposed, achieving a multi-perspective assessment of differential privacy algorithms with a comprehensive score and level as assessment results. Starting from five aspects—algorithm security, feasibility, privacy bias, data utility, and user experience, an indicator system was established. Fuzzy theory was employed to handle uncertainties, while the diagram was used to propagate interactions between factors. The assessment score and level were obtained by calculating the fuzzy influence diagram, and then used as feedback for parameter adjustment to achieve iterative assessment. Formalization link was proposed to solve the problem of completely opposite algorithms with idential evaluation results. Comparative experiments on electricity-carbon analysis model demonstrate the proposed method can assess the protection effectiveness of differential privacy algorithms effectively. Ablation experiments further show that the formalization link plays a key role in the discrimination of the algorithm. © 2024 Editorial Board of Journal on Communications. All rights reserved.
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页码:1 / 19
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