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Privacy Preserving Interactive Record Linkage (PPIRL)

Presented by: 
Hye-Chung Kum Texas A&M University, UNC Chapel Hill and RIMS
Date: 
Tuesday 13th September 2016 - 09:30 to 10:00
Venue: 
INI Seminar Room 1
Abstract: 
Record linkage to integrate uncoordinated databases is critical to population informatics research. Balancing privacy protection against the need for high quality record linkage requires a human-machine hybrid system to manage uncertainty in the ever changing streams of chaotic big data safely. We review the literature in record linkage and privacy. In the computer science literature, private record linkage, which investigates how to apply a known linkage function safely is the most published area. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Most recently, a more flexible computerized third party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on (1) decoupling data via encryption, (3) obfuscation via chaffing (addi ng fake data) and universe manipulation, and (3) minimum incremental information disclosure via recoding. Based on this findings, we formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties. Human based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human-machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility.

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University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons