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Finding Highly Similar Regions of Genomic Sequences Through Homomorphic Encryption

Authors
Bataa, MagsarjavSong, SiwooPark, KunsooKim, MiranCheon, Jung HeeKim, Sun
Issue Date
Mar-2024
Publisher
Mary Ann Liebert Inc.
Keywords
highly similar region; homomorphic encryption; privacy-preserving computation; sequence alignment
Citation
Journal of Computational Biology, v.31, no.3, pp 197 - 212
Pages
16
Indexed
SCIE
SCOPUS
Journal Title
Journal of Computational Biology
Volume
31
Number
3
Start Page
197
End Page
212
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/196953
DOI
10.1089/cmb.2023.0050
ISSN
1066-5277
1557-8666
Abstract
Finding highly similar regions of genomic sequences is a basic computation of genomic analysis. Genomic analyses on a large amount of data are efficiently processed in cloud environments, but outsourcing them to a cloud raises concerns over the privacy and security issues. Homomorphic encryption (HE) is a powerful cryptographic primitive that preserves privacy of genomic data in various analyses processed in an untrusted cloud environment. We introduce an efficient algorithm for finding highly similar regions of two homomorphically encrypted sequences, and describe how to implement it using the bit-wise and word-wise HE schemes. In the experiment, our algorithm outperforms an existing algorithm by up to two orders of magnitude in terms of elapsed time. Overall, it finds highly similar regions of the sequences in real data sets in a feasible time.
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