Privacy-preserving Edit Distance on Genomic Data

TL;DR

This paper introduces ESCOT, a privacy-preserving protocol for computing edit distance on genomic data using Oblivious Transfer, enabling secure DNA sequence matching between parties without revealing sensitive information.

Contribution

First application of Oblivious Transfer to privacy-preserving edit distance computation on genomic data, with practical evaluation on real-world datasets.

Findings

Feasible in real-world scenarios over LAN and WAN networks.

Efficient enough for practical use in privacy-sensitive genomic matching.

Demonstrates secure DNA sequence comparison without data leakage.

Abstract

Suppose Alice holds a DNA sequence and Bob owns a database of DNA sequences. They want to determine whether there is a match for the Alice's input in the Bob's database for any purpose such as diagnosis of Alice's disease. However, Alice does not want to reveal her DNA pattern to Bob, since it would enable him to learn private information about her. For the similar reasons, Bob does not want to reveal any information about his database to Alice. This problem has attracted attention from bioinformatics community in order to protect privacy of users and several solutions have been proposed. Efficiency is always a bottleneck in cryptography domain. In this paper, we propose ESCOT protocol to address privacy preserving Edit distance using Oblivious Transfer (OT) for the first time. We evaluate our approach on a genome dataset over both LAN and WAN network. Experimental results confirm feasibility of our approach in real-world scenarios.