大数据环境下差分隐私保护技术及应用

付钰; 俞艺涵; 吴晓平

doi:10.11959/j.issn.1000-436x.2019209

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大数据环境下差分隐私保护技术及应用

综述 | 更新时间：2024-06-05

- 大数据环境下差分隐私保护技术及应用
- Differential privacy protection technology and its application in big data environment
- 通信学报 2019年40卷第10期页码：157-168
- 作者机构：
  
  海军工程大学信息安全系，湖北武汉 430033
- 作者简介：
  
  [ "付钰（1982- ），女，湖北武汉人，博士，海军工程大学副教授、硕士生导师，主要研究方向为信息安全、风险评估。" ]
  [ "俞艺涵（1992- ），男，浙江金华人，海军工程大学博士生，主要研究方向为信息安全、隐私保护。" ]
  [ "吴晓平（1961- ），男，山西新绛人，博士，海军工程大学教授、博士生导师，主要研究方向为信息安全、密码学。" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(SQ2018YFGX210002);国家自然科学基金资助项目(2015CFC867)
- DOI：10.11959/j.issn.1000-436x.2019209
  中图分类号： TP393
- 网络出版日期：2019-10，
  
  纸质出版日期：2019-10-25
- 稿件说明：
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付钰, 俞艺涵, 吴晓平. 大数据环境下差分隐私保护技术及应用[J]. 通信学报, 2019,40(10):157-168.

Yu FU, Yihan YU, Xiaoping WU. Differential privacy protection technology and its application in big data environment[J]. Journal on communications, 2019, 40(10): 157-168.
付钰, 俞艺涵, 吴晓平. 大数据环境下差分隐私保护技术及应用[J]. 通信学报, 2019,40(10):157-168. DOI： 10.11959/j.issn.1000-436x.2019209.

Yu FU, Yihan YU, Xiaoping WU. Differential privacy protection technology and its application in big data environment[J]. Journal on communications, 2019, 40(10): 157-168. DOI： 10.11959/j.issn.1000-436x.2019209.

摘要

大数据中的隐私保护问题是当前网络空间安全领域的一个研究热点，差分隐私保护作为严格且可证明的隐私保护定义，研究其在大数据环境下的应用现状能够为其后续的系统性应用等提供参考与指导。在系统分析差分隐私保护的相关概念与技术特性的基础上，通过对差分隐私保护技术在数据发布与分析、云计算与大数据计算、位置与轨迹服务及社交网络中的应用等进行综述，阐述了当前具有代表性的研究成果并分析了其存在的问题。研究表明，现有成果从差分隐私保护机理、噪声添加机制与位置、数据处理方式等方面对差分隐私保护应用进行了卓有成效的创新与探究，且相关成果在不同场景下实现了交叉应用。最后提出了差分隐私保护在大数据环境下进一步系统性应用还需要注意的四大问题。

Abstract

The privacy protection in big data is a research hotspot in the field of cyberspace security.As a strict and provable definition of privacy protection

studying application status of differential privacy protection in big data environment can provide reference and guidance for its subsequent system applications.Based on the analysis of the related concepts and technical characteristics of differential privacy protection

the application of differential privacy protection technology was reviewed in data distribution and analysis

cloud computing and big data computing

location and trajectory services and social networks

which expounded the current representative research results and analyzed its existing problems.The research shows that the existing results have made effective innovation and exploration of differential privacy protection applications from the aspects of differential privacy protection mechanism

noise addition mechanism and location

and data processing methods

and the related results have been cross-applied in different scenarios.Finally

four major problems that need to be studied in the further systematic application of differential privacy protection in the big data environment are proposed.

关键词

Keywords

references

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