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PAFR: Privacy-Aware Friends Retrieval over Online Social Networks

机译:PAFR:隐私感知朋友在线社交网络中检索

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Online Social Networks (OSNs) are online services that people use to build social relations with other people. Friends retrieval over OSNs is an important activity among users. However, in existing friends retrieval solutions, user may leak private and sensitive information, such as personal data and friends relation. Traditional end-to-end encryption methods can protect users' information, while it is not available for them to share contents with others. In this paper, aiming at preventing attack launched by the service provider, we propose PAFR, a Privacy-Aware Friends Retrieval scheme over OSNs. Inspired by private set interaction protocols, our scheme allows user to upload his encrypted contents to server, obliviously connect with others as friends, and retrieve friends with specific content. In addition, we design a dual-server model where two non-collude servers S_1 and S_2 perform secure sorting protocol to retrieve the ranked relevant friends without learning the underlying query and friends relationship. Compared with the approach with single server holding the whole knowledge of the OSN, each of them only has a part of the information make our scheme achieve a high level of privacy. Both security and performance analysis demonstrate that our scheme has both a very light user workload and a moderate server workload while being secure against user-server collusion.
机译:在线社交网络(OSN)是人们用来与其他人建立社会关系的在线服务。奥斯人的朋友检索是用户之间的重要活动。然而,在现有的朋友检索解决方案中,用户可能会泄漏私有和敏感的信息,例如个人数据和朋友关系。传统的端到端加密方法可以保护用户的信息,而他们不可用它们与其他人共享内容。在本文中,旨在防止服务提供商推出的攻击,我们向PAFR提出PAFR,这是一个隐私意识到的朋友在OSNS上检索方案。灵感来自私有设备交互协议,我们的方案允许用户将其加密内容上载到服务器,不知情与他人连接为朋友,并检索具有特定内容的朋友。此外,我们设计了一个双服务器模型,其中两个非勾结服务器S_1和S_2执行安全排序协议,以检索排名相关的朋友而不学习底层查询和朋友关系。与具有持有OSN的整体知识的单一服务器的方法相比,它们中的每一个只有一部分信息使我们的计划实现高水平的隐私。安全性和性能分析都表明,我们的方案具有非常轻的用户工作负载和适度的服务器工作负载,同时对用户服务器勾结安全。

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