Electrical and Computer Engineering Publications

Document Type

Article

Publication Date

2024

Volume

85

Issue

2214-2126

Journal

Journal of Information Security and Applications

URL with Digital Object Identifier

https://doi.org/10.1016/j.jisa.2024.103861

Abstract

Patient-centric precision medicine requires the analysis of large volumes of genomic data to tailor treatments and medications based on individual-level characteristics. Because the amount of data held by a single institution is limited, researchers may want access to genomic data held by other institutions. Owing to the inherent privacy implications of genomic data, performing comparisons on encrypted data is preferable in certain settings. The Similar patient query (SPQ) is an application that enables a secure search across genomic databases for patients with similar genetic makeup. Query results can be used to draw meaningful conclusions regarding suitable therapies.

However, existing protocols either reveal intermediate computations, such as similarity scores, which can lead to membership-inference attacks, or they realize the ideal Boolean output (similar/not similar) through multiple protocol rounds, requiring the database owners to stay online throughout.

This paper introduces a two-party privacy-preserving approach to perform SPQs across encrypted genomic databases based on secure function extensions of additively homomorphic encryption. In contrast to related works, our scheme enables secure computation of genomic data similarity without an external party in a single round. This is achieved for more than 1000 positions of a genome in a single public key operation of 256-bit security level in the integer factorization setting.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Citation of this paper:

Mounika Pratapa, Aleksander Essex, Secure similar patients query with homomorphically evaluated thresholds, Journal of Information Security and Applications, Volume 85, 2024, 103861, ISSN 2214-2126, https://doi.org/10.1016/j.jisa.2024.103861. (https://www.sciencedirect.com/science/article/pii/S2214212624001637)

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