Literature DB >> 14987147

Zero-check: a zero-knowledge protocol for reconciling patient identities across institutions.

Jules J Berman1.   

Abstract

CONTEXT: Large, multi-institutional studies often involve merging data records that have been de-identified to protect patient privacy. Unless patient identities can be reconciled across institutions, individuals with records held in different institutions will be falsely "counted" as multiple persons when databases are merged.
OBJECTIVE: The purpose of this article is to describe a protocol that can reconcile individuals with records in multiple institutions.
DESIGN: Institution A and Institution B each create a random character string and send it to the other institution. Each institution receives the random string from the other institution and sums it with their own random string, producing a random string common to both institutions (RandA+B). Each institution takes a unique patient identifier and sums it with RandA+B. The product is a random character string that is identical across institutions when the patient is identical in both institutions. A comparison protocol can be implemented as a zero-knowledge transaction, ensuring that neither institution obtains any knowledge of its own patient or of the patient compared at another institution.
RESULTS: The protocol can be executed at high computational speed. No encryption algorithm or 1-way hash algorithm is employed, and there is no need to protect the protocol from discovery.
CONCLUSION: A zero-knowledge protocol for reconciling patients across institutions is described. This protocol is one of many computational tools that permit pathologists to safely share clinical and research data.

Entities:  

Mesh:

Year:  2004        PMID: 14987147     DOI: 10.5858/2004-128-344-ZAZPFR

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  4 in total

1.  Composite Bloom Filters for Secure Record Linkage.

Authors:  Elizabeth Ashley Durham; Murat Kantarcioglu; Yuan Xue; Csaba Toth; Mehmet Kuzu; Bradley Malin
Journal:  IEEE Trans Knowl Data Eng       Date:  2014-12       Impact factor: 6.977

2.  Quantifying the Correctness, Computational Complexity, and Security of Privacy-Preserving String Comparators for Record Linkage.

Authors:  Elizabeth Durham; Yuan Xue; Murat Kantarcioglu; Bradley Malin
Journal:  Inf Fusion       Date:  2012-10-01       Impact factor: 12.975

3.  A Protocol for the secure linking of registries for HPV surveillance.

Authors:  Khaled El Emam; Saeed Samet; Jun Hu; Liam Peyton; Craig Earle; Gayatri C Jayaraman; Tom Wong; Murat Kantarcioglu; Fida Dankar; Aleksander Essex
Journal:  PLoS One       Date:  2012-07-02       Impact factor: 3.240

4.  Privacy-preserving record linkage using Bloom filters.

Authors:  Rainer Schnell; Tobias Bachteler; Jörg Reiher
Journal:  BMC Med Inform Decis Mak       Date:  2009-08-25       Impact factor: 2.796

  4 in total

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