Paper 2017/207 Original: eprint.iacr.org/2017/207 ↗

Private Queries on Encrypted Genomic Data

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.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Preprint.
History
2017-03-01: last updated
2017-03-01: published
Short URL
https://ia.cr/2017/207
License
https://creativecommons.org/licenses/by/4.0/

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},
      url = {https://eprint.iacr.org/2017/207}
}
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