Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram
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...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2024-08-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024122/ |
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| _version_ | 1841539240434860032 |
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| author | TIAN Yuechi LI Fenghua ZHOU Zejun SUN Zhe GUO Shoukun NIU Ben |
| author_facet | TIAN Yuechi LI Fenghua ZHOU Zejun SUN Zhe GUO Shoukun NIU Ben |
| author_sort | TIAN Yuechi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e85f69f534534bddbd66d06c6f36ac58 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-08-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-e85f69f534534bddbd66d06c6f36ac582025-01-14T07:24:53ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-08-014511969426199Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagramTIAN YuechiLI FenghuaZHOU ZejunSUN ZheGUO ShoukunNIU BenIn 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.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024122/privacy protection effectivenesscomprehensive assessmentfuzzy influence diagramdifferential privacy |
| spellingShingle | TIAN Yuechi LI Fenghua ZHOU Zejun SUN Zhe GUO Shoukun NIU Ben Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram Tongxin xuebao privacy protection effectiveness comprehensive assessment fuzzy influence diagram differential privacy |
| title | Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram |
| title_full | Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram |
| title_fullStr | Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram |
| title_full_unstemmed | Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram |
| title_short | Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram |
| title_sort | assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram |
| topic | privacy protection effectiveness comprehensive assessment fuzzy influence diagram differential privacy |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024122/ |
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