Paper 2017/955

Towards Practical Privacy-Preserving Genome-Wide Association Study

Charlotte Bonte, Eleftheria Makri, Amin Ardeshirdavani, Jaak Simm, Yves Moreau, and Frederik Vercauteren

Abstract

The deployment of Genome-wide association studies (GWASs) requires genomic information of a large population to produce reliable results. This raises significant privacy concerns, making people hesitate to contribute their genetic information to such studies. We propose two provably secure solutions to address this challenge: (1) a somewhat homomorphic encryption approach, and (2) a secure multiparty computation approach. Unlike previous work, our approach does not rely on adding noise to the input data, nor does it reveal any information about the patients. Our protocols calculate the $\chi^2$ statistic in a privacy-preserving manner, without revealing any information other than the significance of the statistic; hence not even the statistic value itself. We significantly increased the efficiency of our protocols by introducing a new masking technique to perform the secure comparison. Our implementations demonstrated that both approaches are efficient. The secure multiparty computation technique completes its execution in approximately 2~ms for data contributed by one million subjects.

Note: The order of the authors needed to be changed to be consistent with the shorter version of our article.