Manual for Using Homomorphic Encryption for Bioinformatics

Biological data science is an emerging field facing multiple challenges for hosting, sharing, computing on, and interacting with large data sets. Privacy regulations and concerns about the risks of leaking sensitive personal health and genomic data add another layer of complexity to the problem. Rec...

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Bibliographic Details
Published inProceedings of the IEEE Vol. 105; no. 3; pp. 552 - 567
Main Authors Dowlin, Nathan, Gilad-Bachrach, Ran, Laine, Kim, Lauter, Kristin, Naehrig, Michael, Wernsing, John
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Bioinformatics
Biology
Cryptography
data privacy
Encryption
Genomics
homomorphic encryption
Public key
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Summary:Biological data science is an emerging field facing multiple challenges for hosting, sharing, computing on, and interacting with large data sets. Privacy regulations and concerns about the risks of leaking sensitive personal health and genomic data add another layer of complexity to the problem. Recent advances in cryptography over the last five years have yielded a tool, homomorphic encryption, which can be used to encrypt data in such a way that storage can be outsourced to an untrusted cloud, and the data can be computed on in a meaningful way in encrypted form, without access to decryption keys. This paper introduces homomorphic encryption to the bioinformatics community, and presents an informal "manual" for using the Simple Encrypted Arithmetic Library (SEAL), which we have made publicly available for bioinformatic, genomic, and other research purposes.
ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2016.2622218