Encrypted Cancer Genomics: Benchmark Reveals Speed Versus Storage Tradeoff

A new benchmarking study in BMC Bioinformatics examines how to protect cancer genomics data when it’s processed in the cloud. The research focuses on fully homomorphic encryption (FHE), which allows computations on encrypted data without decrypting it first, but at a potential cost. Conducted by Dilen Shankar at Anna University in Chennai, India, the work compares two of the most widely used FHE schemes: BFV and CKKS. The study reviews differential expression analysis, explaining why uploading raw RNA-seq count matrices can expose identifying information. It finds a key tradeoff: FHE can slow calculations dramatically, and performance depends on how each scheme handles integers versus approximate real numbers and on rescaling noise accumulation in CKKS under certain parameters.