Manual for Using Homomorphic Encryption for Bioinformatics: This paper provides a new homomorphic encryption algorithm and associated software for bioinformatics to enhance the security and privacy associated with computing on human genomes

Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine, Kristin Lauter, Michael Naehrig, John Wernsing

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number7843616
Pages (from-to)552-567
Number of pages16
JournalProceedings of the IEEE
Volume105
Issue number3
DOIs
StatePublished - Mar 2017
Externally publishedYes

Keywords

  • Bioinformatics
  • cryptography
  • data privacy
  • homomorphic encryption
  • public key

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering

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