Poster: Privacy-preserving Genome Analysis using Verifiable Off-Chain Computation

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Abstract

Genome-wide association studies (GWAS) focus on finding associations between genotypes and phenotypes such as susceptibility to diseases. Since genetic data is extremely sensitive and long-lived, individuals and organizations are reluctant to share their data for analysis. This paper proposes two solutions for a fully decentralized and privacy-preserving system for performing minor allele frequency analysis on multiple data sets. Homomorphic encryption and zero-knowledge proofs are used in combination with a blockchain system to achieve data privacy and enable verifiability. Preliminary evaluation of the solutions reveals several important challenges such as handling large cipher texts in smart contracts and reuse of the encrypted data for specific researcher queries that need to be tackled in order to make the solutions more practical.

Original languageEnglish
Title of host publicationCCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages3475-3477
Number of pages3
ISBN (Electronic)9781450394505
DOIs
Publication statusPublished - 7-Nov-2022
Event28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022 - Los Angeles, United States
Duration: 7-Nov-202211-Nov-2022

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022
Country/TerritoryUnited States
CityLos Angeles
Period07/11/202211/11/2022

Keywords

  • blockchain
  • genomics
  • privacy-preserving protocols
  • smart contracts

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