Security and Correctness Analysis on Privacy-Preserving k-Means Clustering Schemes
Security and Correctness Analysis on Privacy-Preserving k-Means Clustering Schemes
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DOI：
10.1587/transfun.e92.a.1246
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发表时间：
2009-04
期刊：
影响因子：
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通讯作者：
Chunhua Su;F. Bao;Jianying Zhou;T. Takagi;K. Sakurai
中科院分区：
文献类型：
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作者：
Chunhua Su;F. Bao;Jianying Zhou;T. Takagi;K. Sakurai
由于互联网及相关IT技术的快速发展，访问大量数据变得越来越容易。 k 均值聚类是数据挖掘中一种强大且常用的技术。发表了许多关于保护隐私的 k 均值聚类的研究论文。在本文中，我们分析了现有的基于密码技术的隐私保护 k 均值聚类方案。我们证明这些方案会导致隐私泄露，并且由于协议构造的错误而无法输出正确的结果。此外，我们分析了我们的建议作为改善此类问题的选项，但在计算过程中存在中间信息泄露。
Due to the fast development of Internet and the related IT technologies, it becomes more and more easier to access a large amount of data. k-means clustering is a powerful and frequently used technique in data mining. Many research papers about privacy-preserving k-means clustering were published. In this paper, we analyze the existing privacy-preserving k-means clustering schemes based on the cryptographic techniques. We show those schemes will cause the privacy breach and cannot output the correct results due to the faults in the protocol construction. Furthermore, we analyze our proposal as an option to improve such problems but with intermediate information breach during the computation.