大数据隐私保护技术综述

方滨兴; 贾焰; 李爱平; 江荣

doi:10.11959/j.issn.2096-0271.2016001

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大数据隐私保护技术综述

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- 大数据隐私保护技术综述
- Privacy preservation in big data:a survey
- 大数据 2016年2卷第1期页码：2016001
- 作者机构：
  
  1. 北京邮电大学，北京 100876
  2. 国防科学技术大学计算机学院，湖南长沙 410073
- 作者简介：
  
  [ "方滨兴（1960-），男，博士，中国工程院院士，主要研究方向为大数据、计算机网络和信息安全。" ]
  [ "贾焰（1960-），女，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。" ]
  [ "李爱平（1974-），男，博士，国防科学技术大学研究员，主要研究方向为大数据分析、数据挖掘和网络信息安全。" ]
  [ "江荣（1984-），男，博士，国防科学技术大学助理研究员，主要研究方向为隐私保护和网络信息安全。" ]
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2016001
  中图分类号： TP309
- 网络首发：2016-01，
  
  纸质出版：2016-01-20
- 稿件说明：
移动端阅览
方滨兴, 贾焰, 李爱平, 等. 大数据隐私保护技术综述[J]. 大数据, 2016,2(1):2016001.

Binxing FANG, Yan JIA, Aiping LI, et al. Privacy preservation in big data:a survey[J]. BIG DATA RESEARCH, 2016, 2(1): 2016001.
方滨兴, 贾焰, 李爱平, 等. 大数据隐私保护技术综述[J]. 大数据, 2016,2(1):2016001. DOI： 10.11959/j.issn.2096-0271.2016001.

Binxing FANG, Yan JIA, Aiping LI, et al. Privacy preservation in big data:a survey[J]. BIG DATA RESEARCH, 2016, 2(1): 2016001. DOI： 10.11959/j.issn.2096-0271.2016001.

摘要

大数据分析带来的隐私泄露问题日趋严重，如何在利用大数据为各行各业服务的同时，保护隐私数据和防止敏感信息泄露成为新的挑战。大数据具有规模大、来源多、动态更新等特点，传统的隐私保护技术大都已不再适用。为此，给出了大数据时代的隐私概念和生命周期保护模型；从大数据生命周期的发布、存储、分析和使用4个阶段出发，对大数据隐私保护中的技术现状进行了分类阐述，并对各技术的优缺点、适用范围等进行分析；对大数据隐私保护技术发展的方向和趋势进行了阐述。

Abstract

Privacy disclosure issue becomes more and more serious due to big data analysis.Privacy-preserving techniques should be conductive to the big data applications while preserving data privacy.Since big data has the characteristics of huge scale

numerous sources and dynamic update

most traditional privacy preserving technologies are not suitable any more.Therefore

the concept of privacy and life cycle protection model of big data era were introduced firstly.Technical state of big data privacy preservation was elaborated from the points of view of four stages in big data life cycle

i.e.data publishing

storage

analysis and use.The relative merits and scope of application of each technology were investigated as well.Finally

some important direction and tendency of privacy preservation technologies for big data were suggested.

关键词

Keywords

references

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