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  • 标题:Privacy Preserving Linear Regression on Distributed Databases
  • 本地全文:下载
  • 作者:Fida K. Dankar
  • 期刊名称:Transactions on Data Privacy
  • 印刷版ISSN:1888-5063
  • 电子版ISSN:2013-1631
  • 出版年度:2015
  • 卷号:8
  • 期号:1
  • 页码:3-28
  • 出版社:IIIA-CSIC
  • 摘要:Studies that combine data from multiple sources can tremendously improve the outcome of the statistical analysis. However, combining data from these various sources for analysis poses privacy risks. A number of protocols have been proposed in the literature to address the privacy concerns; however they do not fully deliver on either privacy or complexity. In this paper, we present a (theoretical) privacy preserving linear regression model for the analysis of data owned by several sources. The protocol uses a semi-trusted third party and delivers on privacy and complexity
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