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Research on Co-Location Privacy-Preserving System

机译:协同定位隐私保护系统研究

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With the deep integration of mobile, social and location, users share information with location tags and friends labels in mobile social networks, which could result in the disclosure of location privacy of the users and their friends. Because of the complexity of social circles and the difference of relation strength, users have different location privacy-preserving requirements for different friends. Existing location privacy protection methods and mobile social network services pay less attention to the co-location information attack called CF attack for short. A co-location privacy-preserving system framework is proposed, the key technologies of core module called location privacy-preserving agent are explored, novel calculation method of relation strength based on bi-direction interaction frequency between user and friends is given, and two location privacy-preserving algorithms as a defence against CF attack are designed in the paper, which are LPPC based on the user's coordination and CCTA based on the co-location information concealment and time adjustment. Experimental tests on real data sets show that algorithms proposed could be suitable for different location privacy-preserving scenarios and reflect the mapping between intimacy and privacy-preserving requirement effectively, and the system framework could be extended to the location privacy-preserving application for any mobile social network services.
机译:随着移动,社交和位置的深度集成,用户在移动社交网络中与位置标签和朋友标签共享信息,这可能导致用户及其朋友的位置隐私泄露。由于社交圈的复杂性和关系强度的差异,用户对不同的朋友有不同的位置隐私保护要求。现有的位置隐私保护方法和移动社交网络服务很少关注称为CF攻击的共址信息攻击。提出了一种协同定位隐私保护系统框架,探讨了核心模块位置保密代理的关键技术,提出了一种基于用户与好友之间双向交互频率的关系强度计算新方法,并确定了两个位置本文设计了一种隐私保护算法来防御CF攻击,该算法是基于用户协调的LPPC和基于同位信息隐藏和时间调整的CCTA。对真实数据集的实验测试表明,所提出的算法可以适用于不同的位置隐私保护场景,并有效反映了亲密关系和隐私保护需求之间的映射关系,并且该系统框架可以扩展到任何移动设备的位置隐私保护应用程序。社交网络服务。

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