Year: 2025
Type: article
Abstract: ABSTRACT Next‐generation sequencing (NGS) technology has revolutionized human genome research, significantly advancing the field of genetics. NGS provides unmatched abilities to analyze DNA and RNA molecules efficiently and cost‐effectively, transforming genomics research. This technology detects specific alleles within tissues, allowing for accurate diagnoses of genetic mutation‐related diseases. However, the sensitivity of genetic information necessitates careful protection across different usage scenarios. In this paper, we introduce an efficient protocol for privacy‐preserving genetic matching based on the Private Set Intersection (PSI) technique. Our protocol allows genetic diagnoses without disclosing individual genetic data, offering greater security than previous methods that required external server storage or processing of genetic data. By keeping the data on the individuals local device, we reduce the risks associated with cloud storage. The protocol uses a collision‐resistant cuckoo hash table and symmetric encryption methods, ensuring data accuracy and error‐free genetic matching diagnoses. Moreover, our protocol is lightweight, utilizing minimal encryption components to maintain security while minimizing computational complexity and client‐side load. Experimental results demonstrate that our protocol enhances performance by approximately 31.135% compared to similar protocols on average. These attributes make our PSI‐based protocol a robust solution for privacy‐preserving genetic matching, safeguarding sensitive genetic information while meeting the efficiency needs of practical applications.
DOI: 10.1002/cpe.70235
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Award: G2235372276
OpenAlex ID: W4413456118