Secure Collapsing Method Based on Fully Homomorphic Encryption

In this paper, we propose a new approach for performing privacy-preserving genome-wide association study (GWAS) in cloud environments. This method allows a Genomic Research Unit (GRU) who possesses genetic variants of diseased individuals (cases) to compare his/her data against genetic variants of healthy individuals (controls) from a Genomic Research Center (GRC). The originality of this work stands on a secure version of the collapsing method based on the logistic regression model considering that all data of GRU are stored into the cloud. To do so, we take advantage of fully homomorphic encryption and of secure multiparty computation. Experiment results carried out on real genetic data using the BGV cryptosystem indicate that the proposed scheme provides the same results as the ones achieved on clear data.