Paper 2017/207

Private Queries on Encrypted Genomic Data

Gizem S Cetin, Hao Chen, Kim Laine, Kristin Lauter, Peter Rindal, and 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.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Published elsewhere. To appear in BMC Medical Genomics, 2017
Keywords
homomorphic encryptiongenome privacy
Contact author(s)
kim laine @ gmail com
History
2017-03-01: received
Short URL
https://ia.cr/2017/207
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2017/207,
      author = {Gizem S Cetin and Hao Chen and Kim Laine and Kristin Lauter and Peter Rindal and Yuhou Xia},
      title = {Private Queries on Encrypted Genomic Data},
      howpublished = {Cryptology ePrint Archive, Paper 2017/207},
      year = {2017},
      note = {\url{https://eprint.iacr.org/2017/207}},
      url = {https://eprint.iacr.org/2017/207}
}
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