GENOSHARE: Using Avatars to Preserve Privacy on Genomics Pandora

The growing availability of genomic data is revolutionizing both genomic research and medical practice by enabling what is referred to as precision medicine. Yet, one major obstacle to the development of precision medicine to its full potential is the privacy concerns related to genomicdata sharing. Unfortunately, no solution that protects genomic privacy and, at the same time, preserves data utility has been developed so far. In this paper we introduce GENOSHARE, a comprehensive tool for systematically reasoninig about inference attacks on genomic data, and that enables privacy-aware sharing of such data, i.e., sharing that respects individuals’ privacy preferences. GENOSHARE considers the risk of disclosure of sensitive attributes via attacks based on genotype, membership, and kinship inference; by using novel genomic risk-oriented metrics, it raises an alarm when an individual’s privacy policy is at risk of being violated. GENOSHARE also protects individuals’ data from inferences that could be made from the denial of data requests by using avatar genomes, instead of the real genomes. We demonstrate that different inference attacks can benefit from each other and we show the effectiveness of GENOSHARE at detecting possible inferences related to genotypes on real data from the 1000 Genomes Project.