Anonymizing Social Network Using Bipartite Graph
Anonymizing Social Network Using Bipartite Graph
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DOI：
10.1109/iccis.2010.245
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发表时间：
2010-12
期刊：
影响因子：
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通讯作者：
Lihui Lan;Shi-guang Ju;Hua Jin
中科院分区：
文献类型：
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作者：
Lihui Lan;Shi-guang Ju;Hua Jin
社交网络应用对于共享信息已经变得流行。社交网络数据通常包含用户的隐私信息。因此，隐私保护技术应该用来保护社交网络免受各种隐私泄露和攻击。在本文中，我们给出了一种方法来匿名社交网络，可以表示为二分图。我们提出了自同构发布，以防止多种结构攻击，并开发了一个BKM算法。我们在二分图数据上进行实验，研究效用和信息损失度量。
Social networks applications have become popular for sharing information. Social networks data usually contain users'private information. So privacy preservation technologies should be exercised to protect social networks against various privacy leakages and attacks. In this paper, we give an approach for anonymizing social networks which can be represented as bipartite graphs. We propose automorphism publication to protect against multiple structural attacks and develop a BKM algorithm. We perform experiments on bipartite graph data to study the utility and information loss measure.