Security and Correctness Analysis on Privacy-Preserving k-Means Clustering Schemes

Chunhua SU  Feng BAO  Jianying ZHOU  Tsuyoshi TAKAGI  Kouichi SAKURAI  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E92-A   No.4   pp.1246-1250
Publication Date: 2009/04/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Cryptography and Information Security
Keyword: 
privacy-preserving,  k-means clustering,  security analysis,  

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Summary: 
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.