Security and correctness analysis on privacy-preserving k-means clustering schemes

Chunhua Su, Feng Bao, Jianying Zhou, Tsuyoshi Takagi, Kouichi Sakurai

研究成果: ジャーナルへの寄稿学術誌査読

8 被引用数 (Scopus)

抄録

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.

本文言語英語
ページ(範囲)1246-1250
ページ数5
ジャーナルIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
E92-A
4
DOI
出版ステータス出版済み - 2009

!!!All Science Journal Classification (ASJC) codes

  • 信号処理
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • 電子工学および電気工学
  • 応用数学

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