SecureED: Secure Multiparty Edit Distance for Genomic Sequences

DNA edit distance (ED) measures the minimum number of single nucleotide insertions, substitutions, or deletions required to convert a DNA sequence into another. ED has broad applications in healthcare such as sequence alignment, genome assembly, functional annotation, and drug discovery. Privacy-preserving computation is essential in this context to protect sensitive genomic data. Nonetheless, the existing secure DNA edit distance solutions lack efficiency when handling large data sequences or resort to approximations and fail to accurately compute the metric. In this work, we introduce ScureED, a protocol that tackles these limitations, resulting in a significant performance enhancement of approximately 2-24 times compared to existing methods. Our protocol computes a secure ED between two genomes, each comprising 1,000 letters, in just a few seconds. The underlying technique of our protocol is a novel approach that transforms the established approximate matching technique (i.e., the Ukkonen algorithm) into exact matching, exploiting the inherent similarity in human DNA to achieve cost-effectiveness. Furthermore, we introduce various optimizations tailored for secure computation in scenarios with a limited input domain, such as DNA sequences composed solely of the four nucleotide letters.

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Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-03-07
DOI
https://doi.org/10.56553/popets-2025-0072
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

SecureED: Secure Multiparty Edit Distance for Genomic Sequences

Dimitris Mouris, Ni Trieu, Duong Tung Nguyen, Jiahui Gao et al.
Proceedings on Privacy Enhancing Technologies
Cancer Genomics and Diagnostics
article

SecureED: Secure Multiparty Edit Distance for Genomic Sequences

Dimitris Mouris, Ni Trieu, Duong Tung Nguyen, Jiahui Gao, Yagaagowtham Palanikumar
article en

Abstract

DNA edit distance (ED) measures the minimum number of single nucleotide insertions, substitutions, or deletions required to convert a DNA sequence into another. ED has broad applications in healthcare such as sequence alignment, genome assembly, functional annotation, and drug discovery. Privacy-preserving computation is essential in this context to protect sensitive genomic data. Nonetheless, the existing secure DNA edit distance solutions lack efficiency when handling large data sequences or resort to approximations and fail to accurately compute the metric. In this work, we introduce ScureED, a protocol that tackles these limitations, resulting in a significant performance enhancement of approximately 2-24 times compared to existing methods. Our protocol computes a secure ED between two genomes, each comprising 1,000 letters, in just a few seconds. The underlying technique of our protocol is a novel approach that transforms the established approximate matching technique (i.e., the Ukkonen algorithm) into exact matching, exploiting the inherent similarity in human DNA to achieve cost-effectiveness. Furthermore, we introduce various optimizations tailored for secure computation in scenarios with a limited input domain, such as DNA sequences composed solely of the four nucleotide letters.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(2)
Arizona State University (US)
Openalex Percentile: Top 95%
Cancer Genomics and Diagnostics
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SecureED: Secure Multiparty Edit Distance for Genomic Sequences — Dimitris Mouris, Ni Trieu, et al. · Proceedings on Privacy Enhancing Technologies (2025) | TGRS Research Map | TGRS