Welcome to the resource topic for 2017/207
Title:
Private Queries on Encrypted Genomic Data
Authors: Gizem S Cetin, Hao Chen, Kim Laine, Kristin Lauter, Peter Rindal, Yuhou Xia
Abstract:One of the tasks in the iDASH Secure Genome Analysis Competition in 2016 was to demonstrate the feasibility of privacy-preserving queries on homomorphically encrypted genomic data. More precisely, given a list of up to 100,000 mutations, the task was to encrypt the data using homomorphic encryption in a way that allows it to be stored securely in the cloud, and enables the data owner to query the dataset for the presence of specific mutations, without revealing any information about the dataset or the queries to the cloud. We devise a novel string matching protocol that works particularly nicely with homomorphically encrypted data, and show how it yields an efficient solution to the competition task. The protocol we describe is also of independent interest to the homomorphic encryption community, as it can be applied just as well to any kind of data.
ePrint: https://eprint.iacr.org/2017/207
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