Retrieving Hidden Friends: A Collusion Privacy Attack Against Online Friend Search Engine
Retrieving Hidden Friends: A Collusion Privacy Attack Against Online Friend Search Engine
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DOI：
10.1109/tifs.2018.2866309
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发表时间：
2019-04
影响因子：
6.8
通讯作者：
Yuhong Liu;Na Li
中科院分区：
文献类型：
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作者：
Yuhong Liu;Na Li
在线社交网络（OSN）正在为人类用户提供与家人、朋友甚至陌生人交互的各种应用。朋友搜索引擎就是这样一个应用程序，它允许公众查询个人用户的朋友列表，最近越来越受欢迎。然而，如果没有适当的设计，这个应用程序可能会错误地泄露用户的私人关系信息。我们之前的工作已经提出了一个隐私保护解决方案，可以有效地提高OSN的社交性，同时保护用户的友谊隐私免受个人恶意请求者发起的攻击。在本文中，我们提出了一种先进的共谋攻击，受害者用户的友谊隐私可以通过一系列精心设计的查询协调发起多个恶意请求者受到损害。通过合成和真实世界的社交网络数据集验证了所提出的共谋攻击的效果。对高级共谋攻击的深入研究将有助于我们在不久的将来设计出一个更健壮、更安全的OSN好友搜索引擎。
Online social networks (OSNs) are providing a variety of applications for human users to interact with families, friends, and even strangers. One such application, the friend search engine, allows the general public to query individual users’ friend lists and has been gaining popularity recently. However, without proper design, this application may mistakenly disclose users’ private relationship information. Our previous work has proposed a privacy preservation solution that can effectively boost OSNs’ sociability while protecting users’ friendship privacy against attacks launched by individual malicious requestors. In this paper, we propose an advanced collusion attack, where a victim user’s friendship privacy can be compromised through a series of carefully designed queries coordinately launched by multiple malicious requestors. The effect of the proposed collusion attack is validated through synthetic and real-world social network data sets. The in-depth research on the advanced collusion attacks will help us design a more robust and secure friend search engine on OSNs in the near future.