Date of Award

1-1-2019

Document Type

Thesis

Degree Name

M.S.

Department

Computer Science

First Advisor

Rinku Dewri, Ph.D.

Second Advisor

Matt Rutherford, Ph.D.

Third Advisor

Yun-Bo Yi, Ph.D.

Keywords

Elliptic curve cryptography, Federated query processing, Private record linkage

Abstract

Federated query processing for an electronic health record infrastructure enables large epidemiology studies using data integrated from geographically dispersed medical institutions. However, government imposed privacy regulations prohibit disclosure of patient's health record outside the context of clinical care, thereby making it difficult to determine which records correspond to the same entity in the process of query aggregation.

Privacy-preserving record linkage is an actively pursued research area to facilitate the linkage of database records under the constraints of regulations that do not allow the linkage agents to learn sensitive identities of record owners. In earlier works, scalability has been shown to be possible using traditional cryptographic transformations such as Pohlig-Hellman ciphers, precomputations, data parallelism, and probabilistic key reuse approaches.

This work proposes further optimizations to improve the runtime of a linkage exercise by adopting elliptic curve based transformations that are mostly additive and multiplicative, instead of exponentiations. The elliptic curve operations are used to improve the precomputation time, eliminate memory intensive comparisons of encrypted values and introduce data structures to detect negative comparisons. This method of record linkage is able to link data sets of the order of a million rows within 15 minutes. The approach has been gauged using synthetic and real world demographics data with parametric studies. We have also assessed the residual privacy risk of the proposed approach.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Provenance

Received from ProQuest

Rights holder

Shreya Dhiren Patel

File size

72 p.

File format

application/pdf

Language

en

Discipline

Computer science

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