Encrypted genomes: advancing personalized medicine with homomorphic encryption - Lee, Bryan Wei Han (Nanyang Technological University, 2024)
The escalating need for privacy in genomic data analysis, amidst the rising prominence of personalized medicine, has catalyzed the exploration of advanced cryptographic solutions. This project delves into the application of Homomorphic Encryption (HE) to secure genomic calculations, ensuring data privacy without compromising the ability to perform essential analyses. Utilizing the Cheon-Kim-Kim-Song (CKKS) scheme via the HElib library, a web-based Graphical User Interface (GUI) was developed to facilitate user-friendly, secure genomic data input and computation within the encrypted domain. Key genomic calculations such as arithmetic operations, average expression level analysis, differential expression ratio computation, and variance in expression levels were successfully executed. Despite the inherent computational overhead associated with HE, the project underscores its viability for secure genomic analysis, offering insights into optimizing performance and expanding computational capabilities for future research. The endeavor not only illustrates the potential of HE in enhancing data privacy in genomic research but also sets the stage for further advancements in the integration of cryptographic techniques within the field of genomics.