Secure and Distributed Assessment of Privacy-Preserving Releases of GWAS

TL;DR

This paper introduces GenDPR, a distributed middleware leveraging Trusted Execution Environments to securely and privately determine which GWAS results can be safely released, aligning with privacy regulations and reducing data transfer.

Contribution

GenDPR is a novel middleware that enables privacy-preserving GWAS result sharing without a central authority, using TEEs for secure, efficient, and regulatory-compliant data release.

Findings

GenDPR matches centralized accuracy in GWAS result disclosure.

It significantly reduces data transfer by exchanging only intermediary results.

It tolerates collusion of all-but-one federation members to protect genomes.

Abstract

Genome-wide association studies (GWAS) identify correlations between the genetic variants and an observable characteristic such as a disease. Previous works presented privacy-preserving distributed algorithms for a federation of genome data holders that spans multiple institutional and legislative domains to securely compute GWAS results. However, these algorithms have limited applicability, since they still require a centralized instance to decide whether GWAS results can be safely disclosed, which is in violation to privacy regulations, such as GDPR. In this work, we introduce GenDPR, a distributed middleware that leverages Trusted Execution Environments (TEEs) to securely determine a subset of the potential GWAS statistics that can be safely released. GenDPR achieves the same accuracy as centralized solutions, but requires transferring significantly less data because TEEs only exchange intermediary results but no genomes. Additionally, GenDPR can be configured to tolerate all-but-one honest-but-curious federation members colluding with the aim to expose genomes of correct members.