Paper 2024/1088 Original: eprint.iacr.org/2024/1088 ↗

HElix: Genome Similarity Detection in the Encrypted Domain

Rostin Shokri
Charles Gouert
Nektarios Georgios Tsoutsos
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 involves users trying to determine if collected DNA samples are similar to DNA sequences hosted in a remote repository, such as checking for disease mutations in patients with monogenic disorders. Nevertheless, end users may be reluctant to upload sensitive DNA sequences, which might reveal private biological information, while the owners of remote genomics repositories are unwilling to share their databases. To address this challenge, we propose a novel Bloom filter approach based on fully homomorphic encryption to preserve the privacy of the genomic data and enable queries directly on ciphertexts. We utilize the Circuit Bootstrapping and CMUX functionality in TFHE to implement the homomorphic indexing required in Bloom filters. Our EDA-inspired techniques can privately determine if a client's DNA sequence exists in a database. We validate our approach across various database sizes and compare directly with related works. We observe up to 4 orders of magnitude faster server evaluation times and many orders of magnitude smaller communication overhead for our methodology.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Preprint.
History
2025-09-04: last updated
2024-07-04: published
Short URL
https://ia.cr/2024/1088
License
https://creativecommons.org/licenses/by/4.0/

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}
}
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