Privacy-Preserving Genetic Relatedness Test
This addresses privacy issues for individuals using direct-to-consumer genetic testing services, but it is incremental as it builds on existing searchable encryption methods.
The paper tackles the problem of privacy concerns in genetic testing by proposing a privacy-preserving genetic relatedness test (PPGRT) protocol that allows a cloud server to perform relatedness tests on encrypted genetic data, with performance evaluation showing practicality.
An increasing number of individuals are turning to Direct-To-Consumer (DTC) genetic testing to learn about their predisposition to diseases, traits, and/or ancestry. DTC companies like 23andme and Ancestry.com have started to offer popular and affordable ancestry and genealogy tests, with services allowing users to find unknown relatives and long-distant cousins. Naturally, access and possible dissemination of genetic data prompts serious privacy concerns, thus motivating the need to design efficient primitives supporting private genetic tests. In this paper, we present an effective protocol for privacy-preserving genetic relatedness test (PPGRT), enabling a cloud server to run relatedness tests on input an encrypted genetic database and a test facility's encrypted genetic sample. We reduce the test to a data matching problem and perform it, privately, using searchable encryption. Finally, a performance evaluation of hamming distance based PP-GRT attests to the practicality of our proposals.