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The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment.

We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy …