Finding Highly Similar Regions of Genomic Sequences Through Homomorphic Encryption

Area of Science:

• Bioinformatics
• Cryptography
• Computational Biology

Background:

• Genomic sequence comparison is fundamental to bioinformatics.
• Cloud computing offers efficient large-scale genomic analysis but poses privacy risks.
• Homomorphic encryption (HE) enables private data analysis in untrusted environments.

Purpose of the Study:

• To develop an efficient algorithm for identifying similar regions in homomorphically encrypted genomic sequences.
• To enhance privacy and security in cloud-based genomic data analysis.

Main Methods:

• Implementation of a novel algorithm using bit-wise and word-wise homomorphic encryption schemes.
• Algorithm designed for efficient computation on encrypted genomic data.

Main Results:

• The proposed algorithm demonstrates a significant performance improvement, outperforming existing methods by up to two orders of magnitude in elapsed time.
• Successful identification of highly similar genomic regions in real datasets within a feasible timeframe.

Conclusions:

• The developed homomorphic encryption algorithm provides a secure and efficient solution for privacy-preserving genomic sequence comparison in the cloud.
• This advancement facilitates large-scale, secure genomic analyses, addressing critical data privacy concerns.