Survey on privacy protection in non-aggregated data sharing
Although there is a great value hidden in the massive data, it can also easily expose user privacy.Aiming at efficiently and securely sharing data from multiple parties and avoiding leakage of user private information, the development of related research and technologies on the non-aggregated data s...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-06-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021120/ |
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| _version_ | 1841539272485634048 |
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| author | Youhuizi LI Yuyu YIN Honghao GAO Yi JIN Xinheng WANG |
| author_facet | Youhuizi LI Yuyu YIN Honghao GAO Yi JIN Xinheng WANG |
| author_sort | Youhuizi LI |
| collection | DOAJ |
| description | Although there is a great value hidden in the massive data, it can also easily expose user privacy.Aiming at efficiently and securely sharing data from multiple parties and avoiding leakage of user private information, the development of related research and technologies on the non-aggregated data sharing field was introduced.Firstly, secure multi-party computing and its technologies were briefly described, including homomorphic encryption, oblivious transfer, secret sharing, etc.Secondly, the federated learning architecture was analyzed from the aspects of source data nodes and transmission optimization.Finally, the existing non-aggregated data sharing frameworks were listed and compared.In addition, the challenges and future potential research directions were summarized, such as complex multi-party scenarios, the balance between optimization and cost, as well as related security risks. |
| format | Article |
| id | doaj-art-47939f4679ce4757878f46f1b77503e8 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-06-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-47939f4679ce4757878f46f1b77503e82025-01-14T07:22:12ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-06-014219521259742370Survey on privacy protection in non-aggregated data sharingYouhuizi LIYuyu YINHonghao GAOYi JINXinheng WANGAlthough there is a great value hidden in the massive data, it can also easily expose user privacy.Aiming at efficiently and securely sharing data from multiple parties and avoiding leakage of user private information, the development of related research and technologies on the non-aggregated data sharing field was introduced.Firstly, secure multi-party computing and its technologies were briefly described, including homomorphic encryption, oblivious transfer, secret sharing, etc.Secondly, the federated learning architecture was analyzed from the aspects of source data nodes and transmission optimization.Finally, the existing non-aggregated data sharing frameworks were listed and compared.In addition, the challenges and future potential research directions were summarized, such as complex multi-party scenarios, the balance between optimization and cost, as well as related security risks.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021120/privacy protectiondata sharingfederated learningsecure multi-party computation |
| spellingShingle | Youhuizi LI Yuyu YIN Honghao GAO Yi JIN Xinheng WANG Survey on privacy protection in non-aggregated data sharing Tongxin xuebao privacy protection data sharing federated learning secure multi-party computation |
| title | Survey on privacy protection in non-aggregated data sharing |
| title_full | Survey on privacy protection in non-aggregated data sharing |
| title_fullStr | Survey on privacy protection in non-aggregated data sharing |
| title_full_unstemmed | Survey on privacy protection in non-aggregated data sharing |
| title_short | Survey on privacy protection in non-aggregated data sharing |
| title_sort | survey on privacy protection in non aggregated data sharing |
| topic | privacy protection data sharing federated learning secure multi-party computation |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021120/ |
| work_keys_str_mv | AT youhuizili surveyonprivacyprotectioninnonaggregateddatasharing AT yuyuyin surveyonprivacyprotectioninnonaggregateddatasharing AT honghaogao surveyonprivacyprotectioninnonaggregateddatasharing AT yijin surveyonprivacyprotectioninnonaggregateddatasharing AT xinhengwang surveyonprivacyprotectioninnonaggregateddatasharing |