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Data Privacy
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Volume 8 Issue 1


Privacy Preserving Linear Regression on Distributed Databases

Fida K. Dankar(a),(b),(*)

Transactions on Data Privacy 8:1 (2015) 3 - 28

Abstract, PDF

(a) Sidra Medical and Research Center, Doha, Qatar.

(b) IBM, Toronto, Canada.

e-mail:fdankar @sidra.org


Abstract

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.

* Corresponding author.

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ISSN: 1888-5063; ISSN (Digital): 2013-1631; D.L.:B-11873-2008; Web Site: http://www.tdp.cat/
Contact: Transactions on Data Privacy; Vicenç Torra; U. of Skövde; PO Box 408; 54128 Skövde; (Sweden); e-mail:tdp@tdp.cat

 


Vicenç Torra, Last modified: 10 : 32 June 27 2015.