通信学报 ›› 2016, Vol. 37 ›› Issue (12): 124-141.doi: 10.11959/j.issn.1000-436x.2016279

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位置隐私保护技术研究进展

万盛1,李凤华1,2,牛犇2(),孙哲2,李晖1   

  1. 1 西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西 西安 710071
    2 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
  • 出版日期:2016-12-25 发布日期:2017-05-15
  • 基金资助:
    国家自然科学基金—广东联合基金资助项目;国家高技术研究发展计划(“863”计划)基金资助项目;国家自然科学基金—青年科学基金资助项目;国家“核高基”科技重大专项基金资助项目

Research progress on location privacy-preserving techniques

Sheng WAN1,Feng-hua LI1,2,Ben NIU2(),Zhe SUN2,Hui LI1   

  1. 1 State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China
    2 State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100195, China
  • Online:2016-12-25 Published:2017-05-15
  • Supported by:
    The National Natural Science Foundation of China—Guangdong Provincial People's Government of the Joint Natural Science Fund Projects;The National High Technology Research and Development Program of China (863Program);The National Natural Science Youth Science Foundation of China;The National Science and Technology Major Project of China

摘要:

日趋流行的基于位置服务(LBS, location-based service)在为人们日常生活带来便利的同时也严重威胁到用户隐私。位置隐私保护技术逐渐成为研究热点,并涌现出大批研究成果。首先介绍位置隐私保护背景知识,包括位置服务应用场景、位置服务体系框架、隐私保护目标和系统构架;接着讨论LBS中的攻击者模型和隐私保护度量指标;然后对4种基于泛化和模糊的LBS隐私保护技术进行深入分析和总结;最后给出了未来LBS隐私保护技术潜在的研究方向。

关键词: 位置服务, 隐私保护, 位置隐私, 隐私度量, 攻击者模型

Abstract:

While providing plenty of convenience for users in daily life, the increasingly popular location-based ser-vice(LBS) posed a serious threat to users' privacy. The research about privacy-preserving techniques for LBS is becoming a hot spot, and there are a large number of research results. First, background information of privacy protection for LBS was introduced, including application scenarios of LBS, the LBS framework, objects of privacy protection and system architectures of privacy protection. Second, adversary models and metrics for privacy protection in LBS was discussed. Third, four types of privacy-preserving techniques based on generalization and obfuscation for LBS were analyzed and summarized thoroughly. Finally, the potential research directions for privacy-preserving techniques for LBS in the future were shown.

Key words: location-based service, privacy protection, location privacy, privacy metrics, adversary model

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