@inproceedings{f6a879f931cb4aa49910b33fcd0ec258,
title = "Poster: Privacy-preserving Genome Analysis using Verifiable Off-Chain Computation",
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.",
keywords = "blockchain, genomics, privacy-preserving protocols, smart contracts",
author = "Leon Visscher and Mohammed Alghazwi and Dimka Karastoyanova and Fatih Turkmen",
note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022 ; Conference date: 07-11-2022 Through 11-11-2022",
year = "2022",
month = nov,
day = "7",
doi = "10.1145/3548606.3563548",
language = "English",
series = "Proceedings of the ACM Conference on Computer and Communications Security",
publisher = "Association for Computing Machinery",
pages = "3475--3477",
booktitle = "CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security",
}