Practical privacy-preserving user profile matching in social networks

2016 IEEE 32nd International Conference on Data Engineering (ICDE) Pub Date : 2016-05-16 DOI:10.1109/ICDE.2016.7498255

X. Yi, E. Bertino, Fang-Yu Rao, A. Bouguettaya

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引用次数: 26

Abstract

In this paper, we consider a scenario where a user queries a user profile database, maintained by a social networking service provider, to find out some users whose profiles are similar to the profile specified by the querying user. A typical example of this application is online dating. Most recently, an online data site, Ashley Madison, was hacked, which results in disclosure of a large number of dating user profiles. This serious data breach has urged researchers to explore practical privacy protection for user profiles in online dating. In this paper, we give a privacy-preserving solution for user profile matching in social networks by using multiple servers. Our solution is built on homomorphic encryption and allows a user to find out some matching users with the help of the multiple servers without revealing to anyone privacy of the query and the queried user profiles. Our solution achieves user profile privacy and user query privacy as long as at least one of the multiple servers is honest. Our implementation and experiments demonstrate that our solution is practical.

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社交网络中实用的隐私保护用户档案匹配

在本文中，我们考虑这样一个场景:用户查询由社交网络服务提供商维护的用户个人资料数据库，以找出一些个人资料与查询用户指定的个人资料相似的用户。这种应用程序的一个典型例子是在线约会。最近，在线数据网站Ashley Madison遭到黑客攻击，导致大量约会用户资料泄露。这种严重的数据泄露促使研究人员探索在线约会中用户资料的实际隐私保护。本文给出了一种基于多服务器的社交网络用户档案匹配的隐私保护解决方案。我们的解决方案建立在同态加密的基础上，允许用户在多个服务器的帮助下找到一些匹配的用户，而不会向任何人泄露查询的隐私和被查询的用户配置文件。只要多个服务器中至少有一个是诚实的，我们的解决方案就可以实现用户配置文件隐私和用户查询隐私。实验结果表明，该方案是可行的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2016 IEEE 32nd International Conference on Data Engineering (ICDE)

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