Multi-level local differential privacy algorithm recommendation framework
Local differential privacy (LDP) algorithm usually assigned the same protection mechanism and parameters to different users.However, it ignored the differences among the device resources and the privacy requirements of different users.For this reason, a multi-level LDP algorithm recommendation frame...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2022-08-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022106/ |
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| _version_ | 1841539969161625600 |
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| author | Hanyi WANG Xiaoguang LI Wenqing BI Yahong CHEN Fenghua LI Ben NIU |
| author_facet | Hanyi WANG Xiaoguang LI Wenqing BI Yahong CHEN Fenghua LI Ben NIU |
| author_sort | Hanyi WANG |
| collection | DOAJ |
| description | Local differential privacy (LDP) algorithm usually assigned the same protection mechanism and parameters to different users.However, it ignored the differences among the device resources and the privacy requirements of different users.For this reason, a multi-level LDP algorithm recommendation framework was proposed.The server and the users’ requirements were considered in the framework, and the multi-users’ differential privacy protections were realized by the server and the users’ multi-level management.The framework was applied to the frequency statistics scenario to form an LDP algorithm recommendation scheme.LDP algorithm was improved to ensure the availability of statistical results, and a collaborative mechanism was designed to protect users’ privacy preferences.The experimental results demonstrate the availability of the proposed scheme. |
| format | Article |
| id | doaj-art-4d17433ca41a4d9fa0fdae0cbd2b7dd1 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-08-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-4d17433ca41a4d9fa0fdae0cbd2b7dd12025-01-14T06:28:54ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-08-0143526459392125Multi-level local differential privacy algorithm recommendation frameworkHanyi WANGXiaoguang LIWenqing BIYahong CHENFenghua LIBen NIULocal differential privacy (LDP) algorithm usually assigned the same protection mechanism and parameters to different users.However, it ignored the differences among the device resources and the privacy requirements of different users.For this reason, a multi-level LDP algorithm recommendation framework was proposed.The server and the users’ requirements were considered in the framework, and the multi-users’ differential privacy protections were realized by the server and the users’ multi-level management.The framework was applied to the frequency statistics scenario to form an LDP algorithm recommendation scheme.LDP algorithm was improved to ensure the availability of statistical results, and a collaborative mechanism was designed to protect users’ privacy preferences.The experimental results demonstrate the availability of the proposed scheme.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022106/local differential privacyresource adaptationpersonalized privacy budget |
| spellingShingle | Hanyi WANG Xiaoguang LI Wenqing BI Yahong CHEN Fenghua LI Ben NIU Multi-level local differential privacy algorithm recommendation framework Tongxin xuebao local differential privacy resource adaptation personalized privacy budget |
| title | Multi-level local differential privacy algorithm recommendation framework |
| title_full | Multi-level local differential privacy algorithm recommendation framework |
| title_fullStr | Multi-level local differential privacy algorithm recommendation framework |
| title_full_unstemmed | Multi-level local differential privacy algorithm recommendation framework |
| title_short | Multi-level local differential privacy algorithm recommendation framework |
| title_sort | multi level local differential privacy algorithm recommendation framework |
| topic | local differential privacy resource adaptation personalized privacy budget |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022106/ |
| work_keys_str_mv | AT hanyiwang multilevellocaldifferentialprivacyalgorithmrecommendationframework AT xiaoguangli multilevellocaldifferentialprivacyalgorithmrecommendationframework AT wenqingbi multilevellocaldifferentialprivacyalgorithmrecommendationframework AT yahongchen multilevellocaldifferentialprivacyalgorithmrecommendationframework AT fenghuali multilevellocaldifferentialprivacyalgorithmrecommendationframework AT benniu multilevellocaldifferentialprivacyalgorithmrecommendationframework |