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计算机工程

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面向位置服务的用户隐私保护

裴媛媛1,2,石润华1,2,仲红1,2,张顺1,2   

  1. (1.安徽大学计算智能与信号处理教育部重点实验室,合肥 230039;2.安徽大学计算机科学与技术学院,合肥 230601)
  • 收稿日期:2014-11-04 出版日期:2015-10-15 发布日期:2015-10-15
  • 作者简介:裴媛媛(1991-),女,硕士研究生,主研方向:信息安全;石润华、仲红,教授、博士生导师;张顺,讲师、博士。
  • 基金资助:
    国家自然科学基金资助项目(61173187,61173188,11301002);安徽省自然科学基金资助项目(11040606M141,1408085QF107);安徽大学博士科研启动经费基金资助项目(33190187);安徽大学“信息安全”新专业基金资助项目(17110099)。

User Privacy Protection for Location-based Service

PEI Yuanyuan 1,2,SHI Runhua 1,2,ZHONG Hong 1,2,ZHANG Shun 1,2   

  1. (1.Key Laboratory of Intelligent Computing & Signal Processing,Ministry of Education,Anhui University,Hefei 230039,China;2.School of Computer Science and Technology,Anhui University,Hefei 230601,China)
  • Received:2014-11-04 Online:2015-10-15 Published:2015-10-15

摘要: 传感器技术和移动通信设备的发展使位置服务(LBS)得到广泛应用。与此同时,在服务过程中所产生的隐私问题也成为关注的焦点。为此,针对LBS位置隐私的保护问题,构造一个用户协作的分布式模型,并设计一种新的隐私保护方案。在构建匿名区时,使用贝叶斯Nash均衡思想以及安全多方求和技术以保证用户信息的隐私。在处理查询结果时,引入Voronoi图的方法以提高查询效率。分析结果表明,该方案考虑了用户节点自私和不可信的情况,并且简化了查询过程,在保护隐私的同时可提高服务的整体性能。

关键词: 位置隐私, 用户协作, 贝叶斯Nash均衡, 安全多方求和, Voronoi图

Abstract: With the development of sensor technology and mobile communication equipments,there appears Location-based Service(LBS),which is widely used.However,privacy issues,which arise in the enjoyment of the services at the same time,are becoming the focus of research.For privacy protection issues in LBS,this paper proposes a distributed model with users’ cooperation and designs a new privacy protection scheme.In this scheme,when constructing the anonymous area,it uses Bayesian Nash equilibrium and secure multiparty summation technologies to ensure the user information privacy.When processing the query results,it introduces the Voronoi map method to increase the query efficiency.Analysis experimental result shows that the proposed scheme gives full consideration to the selfishness and unreliability of users.Hence it not only can provide the protection of user privacy,but also can improve the performance of the services.

Key words: location privacy, user collaboration, Bias Nash equilibrium, secure multiparty summation, Voronoi map

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