Gene Multiple Sequence Alignment is crucial for genomic data analysis, forming the basis for studying its biological significance. The digitization of genomic data allows collaborative analysis on cloud platforms, improving the efficiency and precision of genomic research. However, gene sequences contain sensitive information, posing a risk of privacy leakage with unauthorized access. Balancing privacy, accuracy, and efficiency in multiple sequence alignment for long gene sequences remains a challenge. In this paper, we propose a distributed privacy-preserving multiple sequence alignment scheme for long sequences based on secure multi-party computation. Our scheme includes a method for segmenting long sequences to achieve partially distributed computing and a privacy-preserving method for calculating edit distance among subsequences using secret sharing. The scheme consists of a distributed computing phase and an aggregate computing phase, optimizing efficiency by dropping repeated subsequences alignment. Our proposed scheme achieves accurate and efficient privacy-preserving alignment for long gene sequences.

With the development of bioinformatics technology, there is an increasing demand for gene sequence alignment. Gene sequence alignment can determine the homology between sequences and plays an increasingly prominent role in the traceback of species, the construction of phylogenetic trees and the diagnosis of human diseases. So far, gene sequence alignment schemes usually do not consider the privacy of participants, which could cause the disclosure of sensitive information, thus there is an urgent need for secure gene sequence alignment schemes. In this paper, we model genomic data from the perspective of privacy protection. On this basis, we design a scheme of gene sequence alignment for the analysis of homologous genopathy. Genopathy private query is realized by adding redundant query conditions, and secure gene sequence alignment is realized by using garbled circuit. And we propose merging truth table to implement a garbled equality gate circuit that only needs to send ciphertext once. The times of encryption and decryption reduced to a third of the general garbled equality gate circuit. Consequently, the scheme can protect the data privacy, query privacy and output privacy of both participants and has better practicability.