Paper 2024/1088
HElix: Genome Similarity Detection in the Encrypted Domain
Abstract
As the field of genomics continues to expand and more sequencing data is gathered, genome analysis becomes increasingly relevant for many users. For example, a common scenario entails users trying to determine if their DNA samples are similar to DNA sequences hosted in a larger remote repository. Nevertheless, end users may be reluctant to upload their DNA sequences, while the owners of remote genomics repositories are unwilling to openly share their database. To address this challenge, we propose two distinct approaches based on fully homomorphic encryption to preserve the privacy of the genomic data and enable queries directly on ciphertexts. The first is based on the ubiquitous MinHash algorithm and can determine if similar matches exist in the database, while the second involves a bespoke bloom filter construction for determining exact matches. We validate both approaches across various database sizes using both GPU and CPU-based cloud servers.
Metadata
- Available format(s)
- Category
- Applications
- Publication info
- Preprint.
- Keywords
- Homomorphic encryptionPrivate genome associationMinHashBloom filters
- Contact author(s)
-
rostinsh @ udel edu
cgouert @ udel edu
tsoutsos @ udel edu - History
- 2024-07-05: approved
- 2024-07-04: received
- See all versions
- Short URL
- https://ia.cr/2024/1088
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2024/1088, author = {Rostin Shokri and Charles Gouert and Nektarios Georgios Tsoutsos}, title = {{HElix}: Genome Similarity Detection in the Encrypted Domain}, howpublished = {Cryptology {ePrint} Archive, Paper 2024/1088}, year = {2024}, url = {https://eprint.iacr.org/2024/1088} }