research-article

Privacy-Preserving Linkage of Genomic and Clinical Data Sets

Authors:

Dixie B. Baker,

Bartha M. Knoppers,

David van Enckevort,

Petra Kaufmann,

Hanns Lochmuller,

Domenica TaruscioAuthors Info & Claims

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 16, Issue 4

Pages 1342 - 1348

https://doi.org/10.1109/TCBB.2018.2855125

Published: 01 July 2019 Publication History

Abstract

The capacity to link records associated with the same individual across data sets is a key challenge for data-driven research. The challenge is exacerbated by the potential inclusion of both genomic and clinical data in data sets that may span multiple legal jurisdictions, and by the need to enable re-identification in limited circumstances. Privacy-Preserving Record Linkage PPRL methods address these challenges. In 2016, the Interdisciplinary Committee of the International Rare Diseases Research Consortium IRDiRC launched a task team to explore approaches to PPRL. The task team is a collaboration with the Global Alliance for Genomics and Health GA4GH Regulatory and Ethics and Data Security Work Streams, and aims to prepare policy and technology standards to enable highly reliable linking of records associated with the same individual without disclosing their identity except under conditions in which the use of the data has led to information of importance to the individual's safety or health, and applicable law allows or requires the return of results. The PPRL Task Force has examined the ethico-legal requirements, constraints, and implications of PPRL, and has applied this knowledge to the exploration of technology methods and approaches to PPRL. This paper reports and justifies the findings and recommendations thus far.

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Cited By

Mortl KDewri R(2022)Generating-Set Evaluation of Bloom Filter Hardening Techniques in Private Record LinkageInformation Systems Security10.1007/978-3-031-23690-7_3(44-63)Online publication date: 16-Dec-2022
https://dl.acm.org/doi/10.1007/978-3-031-23690-7_3
Adir AAharoni EDrucker NKushnir EMasalha RMirkin MSoceanu O(2022)Privacy-Preserving Record Linkage Using Local Sensitive Hash and Private Set IntersectionApplied Cryptography and Network Security Workshops10.1007/978-3-031-16815-4_22(398-424)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-16815-4_22
Desmet CCook D(2021)Recent Developments in Privacy-preserving Mining of Clinical DataACM/IMS Transactions on Data Science10.1145/34477742:4(1-32)Online publication date: 15-Nov-2021
https://dl.acm.org/doi/10.1145/3447774
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cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics

IEEE/ACM Transactions on Computational Biology and Bioinformatics Volume 16, Issue 4

July 2019

360 pages

ISSN:1545-5963

Issue’s Table of Contents

Copyright © 2019.

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 July 2019

Published in TCBB Volume 16, Issue 4

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Cited By

Mortl KDewri R(2022)Generating-Set Evaluation of Bloom Filter Hardening Techniques in Private Record LinkageInformation Systems Security10.1007/978-3-031-23690-7_3(44-63)Online publication date: 16-Dec-2022
https://dl.acm.org/doi/10.1007/978-3-031-23690-7_3
Adir AAharoni EDrucker NKushnir EMasalha RMirkin MSoceanu O(2022)Privacy-Preserving Record Linkage Using Local Sensitive Hash and Private Set IntersectionApplied Cryptography and Network Security Workshops10.1007/978-3-031-16815-4_22(398-424)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-16815-4_22
Desmet CCook D(2021)Recent Developments in Privacy-preserving Mining of Clinical DataACM/IMS Transactions on Data Science10.1145/34477742:4(1-32)Online publication date: 15-Nov-2021
https://dl.acm.org/doi/10.1145/3447774
Vatsalan DYu JThorne BHenecka W(2020)P-Signature-Based Blocking to Improve the Scalability of Privacy-Preserving Record LinkageData Privacy Management, Cryptocurrencies and Blockchain Technology10.1007/978-3-030-66172-4_3(35-51)Online publication date: 17-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-66172-4_3

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