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Recent advances in DNA sequencing technologies have put ubiquitousavailability of fully sequenced human genomes within reach. It is no longerhard to imagine the day when everyone will have the means to obtain and storeone's own DNA sequence. Widespread and affordable availability of fullysequenced genomes immediately opens up important opportunities in a number ofhealth-related fields. In particular, common genomic applications and testsperformed in vitro today will soon be conducted computationally, usingdigitized genomes. New applications will be developed as genome-enabledmedicine becomes increasingly preventive and personalized. However, thisprogress also prompts significant privacy challenges associated with potentialloss, theft, or misuse of genomic data. In this paper, we begin to addressgenomic privacy by focusing on three important applications: Paternity Tests,Personalized Medicine, and Genetic Compatibility Tests. After carefullyanalyzing these applications and their privacy requirements, we propose a setof efficient techniques based on private set operations. This allows us toimplement in in silico some operations that are currently performed via invitro methods, in a secure fashion. Experimental results demonstrate thatproposed techniques are both feasible and practical today.

Countering Gattaca: Efficient and Secure Testing of Fully-Sequenced Human Genomes (Full Version)