Privacy preserving linear regression on distributed databases

Fida K. Dankar

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)3-28
Number of pages26
JournalTransactions on Data Privacy
Issue number1
Publication statusPublished - Jan 1 2015
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Statistics and Probability


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