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

Chunhua SU
Feng BAO
Jianying ZHOU
Tsuyoshi TAKAGI

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
DOI: 10.1587/transfun.E92.A.1246
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Cryptography and Information Security
privacy-preserving,  k-means clustering,  security analysis,  

Full Text: PDF>>
Buy this Article

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.