  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.
