Securing Private Data Sharing in Multi-Party Analytics

11 Pages Posted: 30 Jul 2016

See all articles by Gowtham Bellala

Gowtham Bellala

Hewlett-Packard Laboratories, Palo Alto

Bernardo A. Huberman

Stanford University

Date Written: July 29, 2016

Abstract

A general class of problems arises when datasets containing private information belong to multiple parties or owners and they collectively want to perform analytic studies on the entire set while respecting the privacy and security concerns of each individual party. We describe a solution to this problem in the form of a secure procedure for data mapping and/or linkage, which allows to identify the correspondence between entities in a distributed dataset. In contrast to existing methods this solution does not require either a trusted or semi-trusted third party, while being simple, efficient and scalable for both large datasets and number of parties.

Keywords: analytics, security, multiparty

Suggested Citation

Bellala, Gowtham and Huberman, Bernardo A., Securing Private Data Sharing in Multi-Party Analytics (July 29, 2016). Available at SSRN: https://ssrn.com/abstract=2816140 or http://dx.doi.org/10.2139/ssrn.2816140

Gowtham Bellala

Hewlett-Packard Laboratories, Palo Alto ( email )

1501 Page Mill Road
Palo Alto, CA 94301
United States

Bernardo A. Huberman (Contact Author)

Stanford University ( email )

Palo Alto, CA 94305
United States

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