隐私计算研究范畴及发展趋势

李凤华; 李晖; 贾焰; 俞能海; 翁健

doi:10.11959/j.issn.1000-436x.2016078

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隐私计算研究范畴及发展趋势

学术论文 | 更新时间：2024-06-05

- 隐私计算研究范畴及发展趋势
- Privacy computing:concept, connotation and its research trend
- 通信学报 2016年37卷第4期页码：1-11
- 作者机构：
  
  1. 中国科学院信息工程研究所信息安全国家重点实验室，北京100195
  2. 西安电子科技大学网络与信息安全学院，陕西西安710071
  3. 国防科学技术大学计算机学院，湖南长沙410073
  4. 中国科学技术大学信息科学技术学院，安徽合肥230026
  5. 暨南大学信息科学技术学院，广东广州510632
- 作者简介：
  
  [ "李凤华（1966-），男，湖北浠水人，博士，中国科学院信息工程研究所副总工、研究员、博士生导师，主要研究方向为网络与系统安全、信息保护、隐私计算。" ]
  [ "李晖（1968-），男，河南灵宝人，博士，西安电子科技大学教授、博士生导师，主要研究方向为密码学、无线网络安全、云计算安全、信息论与编码理论。" ]
  [ "贾焰（1960-），女，四川成都人，博士，国防科学技术大学教授，主要研究方向为大数据、网络信息安全和社交网络。" ]
  [ "俞能海（1964-），男，安徽无为人，博士，中国科学技术大学教授、博士生导师，主要研究方向为图像处理与媒体内容安全、互联网信息检索与数据挖掘。" ]
  [ "翁健（1976-），男，广东茂名人，博士，暨南大学教授、博士生导师，主要研究方向为密码学与信息安全。" ]
- 基金信息：
  
  国家自然科学基金-广东联合基金资助项目(U1401251);国家111计划基金资助项目(B16037)
- DOI：10.11959/j.issn.1000-436x.2016078
  中图分类号： G643.0
- 网络出版日期：2016-04，
  
  纸质出版日期：2016-04-25
- 稿件说明：
移动端阅览
李凤华, 李晖, 贾焰, 等. 隐私计算研究范畴及发展趋势[J]. 通信学报, 2016,37(4):1-11.

Feng-hua LI, Hui LI, Yan JIA, et al. Privacy computing:concept, connotation and its research trend[J]. Journal of communications, 2016, 37(4): 1-11.
李凤华, 李晖, 贾焰, 等. 隐私计算研究范畴及发展趋势[J]. 通信学报, 2016,37(4):1-11. DOI： 10.11959/j.issn.1000-436x.2016078.

Feng-hua LI, Hui LI, Yan JIA, et al. Privacy computing:concept, connotation and its research trend[J]. Journal of communications, 2016, 37(4): 1-11. DOI： 10.11959/j.issn.1000-436x.2016078.

摘要

随着移动互联网、云计算和大数据技术的广泛应用，电商、搜索、社交网络等服务在提供便利的同时，大数据分析使用户隐私泄露的威胁日益凸显，不同系统隐私保护策略和能力的差异性使隐私的延伸管理更加困难，同一信息的隐私保护需求随时间变化需要多种隐私保护方案的组合协同。目前已有的各类隐私保护方案大多针对单一场景，隐私缺乏定量化的定义，隐私保护的效果、隐私泄露的利益损失以及隐私保护方案融合的复杂性三者之间的关系刻画缺乏系统的计算模型。因此，在分析隐私保护研究现状的基础上，提出隐私计算的概念，对隐私计算的内涵加以界定，从隐私信息的全生命周期讨论隐私计算研究范畴，并从隐私计算模型、隐私保护场景适应的密码理论、隐私控制与抗大数据分析的隐私保护、基于信息隐藏的隐私保护以及支持高并发的隐私保护服务架构等方面展望隐私计算的发展趋势。

Abstract

s: With the widespread application of mobile Internet

cloud computing and big data technologies

people enjoy the convenience of electronic business

information retrieval

social network and other services

whereas the threats of privacy leaks are ever growing due to the use of big data analytics. The differences of privacy protection strategy and ability in different systems bring more difficulties in privacy extended management. In addition

the requirements of pro-tecting the same information at different time need the combination of various privacy protection schemes. However

nearly all the current privacy protection schemes are ing at a single case

which lacks systematic and quantized pri-vacy characterization. Furthermore

there is no systematic computing model describing the relationship between the pro-tection level

profit and loss of privacy leaks and the complexity of integrated privacy protection methods. Based on the analysis on the research status of privacy protection

the concept and connotation of privacy computing is proposed and defined. Then the privacy computing research category will be discussed from the whole life cycle of information privacy protection. Finally

some research directions of privacy computing are given

including privacy computing model

context adaptive cryptology for privacy protection

big data a lytics resisted privacy control and protection

privacy protection based on information hiding and system architecture for high concurrent privacy preserving services.

关键词

Keywords

references

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