Efficient secure primitive for privacy preserving distributed computations

Youwen Zhu, Tsuyoshi Takagi, Liusheng Huang

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

4 被引用数 (Scopus)

抄録

Scalar product protocol aims at securely computing the dot product of two private vectors. As a basic tool, the protocol has been widely used in privacy preserving distributed collaborative computations. In this paper, at the expense of disclosing partial sum of some private data, we propose a linearly efficient Even-Dimension Scalar Product Protocol (EDSPP) without employing expensive homomorphic crypto-system and third party. The correctness and security of EDSPP are confirmed by theoretical analysis. In comparison with six most frequently-used schemes of scalar product protocol (to the best of our knowledge), the new scheme is a much more efficient one, and it has well fairness. Simulated experiment results intuitively indicate the good performance of our novel scheme. Consequently, in the situations where divulging very limited information about private data is acceptable, EDSPP is an extremely competitive candidate secure primitive to achieve practical schemes of privacy preserving distributed cooperative computations. We also present a simple application case of EDSPP.

本文言語英語
ホスト出版物のタイトルAdvances in Information and Computer Security - 7th International Workshop on Security, IWSEC 2012, Proceedings
ページ233-243
ページ数11
DOI
出版ステータス出版済み - 11 9 2012
イベント7th International Workshop on Security, IWSEC 2012 - Fukuoka, 日本
継続期間: 11 7 201211 9 2012

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7631 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他7th International Workshop on Security, IWSEC 2012
国/地域日本
CityFukuoka
Period11/7/1211/9/12

All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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