抗大数据分析的隐私保护：研究现状与进展

仝伟; 毛云龙; 陈庆军; 王彬入; 张保佳; 仲盛

doi:10.11959/j.issn.2096-109x.2016.00042

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抗大数据分析的隐私保护：研究现状与进展

综述 | 更新时间：2024-06-03

- 抗大数据分析的隐私保护：研究现状与进展
- Survey of big-data-analysis-resistant privacy protection
- 网络与信息安全学报 2016年2卷第4期页码：44-55
- 作者机构：
  
  1. 南京大学计算机科学与技术系，江苏南京 210023
  2. 南京大学计算机软件新技术国家重点实验室，江苏南京 210023
- 作者简介：
  
  [ "仝伟（1991-），男，江苏睢宁人，南京大学硕士生，主要研究方向为隐私保护与机制设计。" ]
  [ "毛云龙（1990-），男，吉林安图人，南京大学博士生，主要研究方向为计算机网络、安全与隐私保护、无线网络。" ]
  [ "陈庆军（1991-），男，重庆人，南京大学硕士生，主要研究方向为软件定义网络、移动感知中的隐私保护。" ]
  [ "王彬入（1993-），男，江苏盐城人，南京大学硕士生，主要研究方向为隐私保护和安全博弈。" ]
  [ "张保佳（1991-)，男，江苏沭阳人，南京大学硕士生，主要研究方向为数据完整性验证。" ]
  [ "仲盛（1974-），男，江苏南京人，博士，南京大学教授、博士生导师，主要研究方向为密码学、博弈论及其在计算机网络、分布式系统中的应用。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61321491);国家自然科学基金资助项目;The National Natural Science Foundation of China(61425024);国家自然科学基金资助项目;The National Natural Science Foundation of China(61300235);国家自然科学基金资助项目;The National Natural Science Foundation of China(61402223);江苏省双创计划基金资助项目;Jiangsu Province Double Innovation Talent Program
- DOI：10.11959/j.issn.2096-109x.2016.00042
  中图分类号： TP309
- 网络首发：2016-04，
  
  纸质出版：2016-04-15
- 稿件说明：
移动端阅览
仝伟, 毛云龙, 陈庆军, 等. 抗大数据分析的隐私保护：研究现状与进展[J]. 网络与信息安全学报, 2016,2(4):44-55.

Wei TONG, AOYun-long M, Qing-jun CEHN, et al. Survey of big-data-analysis-resistant privacy protection[J]. Chinese Journal of Network and Information Security, 2016, 2(4): 44-55.
仝伟, 毛云龙, 陈庆军, 等. 抗大数据分析的隐私保护：研究现状与进展[J]. 网络与信息安全学报, 2016,2(4):44-55. DOI： 10.11959/j.issn.2096-109x.2016.00042.

Wei TONG, AOYun-long M, Qing-jun CEHN, et al. Survey of big-data-analysis-resistant privacy protection[J]. Chinese Journal of Network and Information Security, 2016, 2(4): 44-55. DOI： 10.11959/j.issn.2096-109x.2016.00042.

摘要

隐私保护对于大数据时代的数据分享和利用起到了至关重要的作用。传统的隐私保护方法无法有效地应对在大数据环境中可能存在的数据间的深度关联带来的隐私泄露。因此，需要能够抗大数据分析的隐私保护方法。首先，调研了国内外学者的相关研究工作，并将当前和抗大数据分析的隐私保护相关的工作总结为海量高维异构数据隐私保护、地理位置隐私保护以及高可用性隐私保护发布方案3个方面。其次，着重介绍了南京大学COSEC研究团队在这方面取得的一些研究进展。最后，得到了抗大数据分析的隐私保护的重要性和前瞻性的结论，并介绍了未来可能的研究方向。

Abstract

Privacy protection plays a significant role in big data era for data sharing and analysis.Traditional privacy protection approaches may not apply well for big data scenarios

because there may exist deep associations which can also cause privacy leakages.Therefore

privacy protection mechanisms that can defend against big data analysis is needed.A survey on related works was conducted

and the previous works were classified into three categories:privacy protection for massive high-dimensional heterogeneous data

location privacy protection and privacy protec-tion with enhanced utility.Then

the works in this area by COSEC group from nanjing university were introduced.At last

the privacy protection against big data analysis which was important and forward-looking was concluded

and the possible directions in this research area were introduced.

关键词

Keywords

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