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In this paper, we propose privacy-enhancing technologies for personal use of the genomic data and analyze the tradeoff between genomic privacy and storage cost of the genomes. First, we highlight the potential privacy threats on the genomic data. Then, focusing specifically on a disease-susceptibility test, we develop a new architecture (between the patient and the medical unit) and propose a privacy-preserving algorithm by utilizing homomorphic encryption. Assuming the whole genome sequencing is done by a certified institution, we propose to store patients’ genomic data encrypted by their public keys at a Storage and Processing Unit (SPU). The proposed algorithm lets the SPU process the encrypted genomic data for medical tests while preserving the privacy of patients’ genomic data. We extensively analyze the relationship between the storage cost (of the genomic data), the level of genomic privacy (of the patient), and the characteristics of the genomic data. Furthermore, we show via a complexity analysis the practicality of the proposed scheme.
Tamar Kohn, Xavier Fernandez Cassi