Distributed noise generation for density estimation based clustering without trusted third party

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

抄録

The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suff er from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

本文言語英語
ページ(範囲)1868-1871
ページ数4
ジャーナルIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
E92-A
8
DOI
出版ステータス出版済み - 8月 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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