面向隐私保护的非聚合式数据共享综述

李尤慧子; 殷昱煜; 高洪皓; 金一; 王新珩

doi:10.11959/j.issn.1000-436x.2021120

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面向隐私保护的非聚合式数据共享综述

综述 | 更新时间：2024-06-05

- 面向隐私保护的非聚合式数据共享综述
- Survey on privacy protection in non-aggregated data sharing
- 通信学报 2021年42卷第6期页码：195-212
- 作者机构：
  
  1. 杭州电子科技大学计算机学院，浙江杭州 310018
  2. 上海大学计算机工程与科学学院，上海 200444
  3. 韩国嘉泉大学计算机工程系，城南市 461701
  4. 北京交通大学计算机与信息技术学院，北京 100044
  5. 西交利物浦大学电气与电子工程系，江苏苏州 215123
- 作者简介：
  
  [ "李尤慧子（1989− ），女，河南新蔡人，博士，杭州电子科技大学副教授，主要研究方向为边缘计算、隐私安全、移动互联网计算、高能效系统" ]
  [ "殷昱煜（1980− ），男，重庆人，博士，杭州电子科技大学教授，主要研究方向为边缘计算、服务计算、大数据分析、软件形式化方法等" ]
  [ "高洪皓（1985− ），男，浙江临海人，博士，上海大学副教授、韩国嘉泉大学教授，主要研究方向为软件形式化验证、服务协同计算、无线网络和工业物联网、智能医学影像处理等" ]
  [ "金一（1982− ），女，河北石家庄人，博士，北京交通大学教授、博士生导师，主要研究方向为机器学习与认知计算、人工智能及应用、图像感知与识别" ]
  [ "王新珩（1968− ），男，山东平度人，博士，西交利物浦智能工程学院教授、博士生导师，主要研究方向为物联网、室内定位、智能化服务和智慧城市" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2020YFB2103805);国家自然科学基金资助项目(61802093);国家自然科学基金资助项目(61972358)
- DOI：10.11959/j.issn.1000-436x.2021120
  中图分类号： TN92
- 网络出版日期：2021-06，
  
  纸质出版日期：2021-06-25
- 稿件说明：
移动端阅览
李尤慧子, 殷昱煜, 高洪皓, 等. 面向隐私保护的非聚合式数据共享综述[J]. 通信学报, 2021,42(6):195-212.

Youhuizi LI, Yuyu YIN, Honghao GAO, et al. Survey on privacy protection in non-aggregated data sharing[J]. Journal on communications, 2021, 42(6): 195-212.
李尤慧子, 殷昱煜, 高洪皓, 等. 面向隐私保护的非聚合式数据共享综述[J]. 通信学报, 2021,42(6):195-212. DOI： 10.11959/j.issn.1000-436x.2021120.

Youhuizi LI, Yuyu YIN, Honghao GAO, et al. Survey on privacy protection in non-aggregated data sharing[J]. Journal on communications, 2021, 42(6): 195-212. DOI： 10.11959/j.issn.1000-436x.2021120.

摘要

海量数据价值虽高但与用户隐私关联也十分密切，以高效安全地共享多方数据且避免隐私泄露为目标，介绍了非聚合式数据共享领域的研究发展。首先，简述安全多方计算及其相关技术，包括同态加密、不经意传输、秘密共享等；其次，分析联邦学习架构，从源数据节点和通信传输优化方面探讨现有研究；最后，整理对比面向隐私保护的非聚合式数据共享框架，为后续研究方案构建和运行提供支撑。此外，总结提出非聚合式数据共享领域的挑战和潜在的研究方向，如复杂多参与方场景、优化开销平衡、相关安全隐患等。

Abstract

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.

关键词

Keywords

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