Performance Analysis of HElib on a Privacy Preserving Search for Genome Information with Fully Homomorphic Encryption

Recently, numerous studies have been conducted on the practical implementation of fully homomorphic encryption (FHE) for large data analysis. Many systems using FHE are cloud-based and use many DRAMs because the progression of encryption or bootstrapping increases the time and space complexities. However, DRAMs in the cloud cannot be effectively used because they are shared by several systems and cost us inefficiently. Here, we combine Solid State Drive (SSDs) with DRAMs for an application using FHE. They have several different architectural advantages from DRAMs: they cost less per one bit and have high parallelism. Our primary objective is to utilize SSDs instead of DRAMs and reduce the cost on the cloud when using an application of FHE. This study uses the HElib library and an application for a privacy-preserving search for genome information. First, we identified the bottleneck of this application for using SSDs effectively. We analyzed the features of the application using Hyper-Threading technology and found that it consumes considerable CPU power. It is highly parallel, and the processing of load/store instructions from DRAMs to CPUs in sequential is the bottleneck. Second, we revealed the bottleneck in detail by the function in HElib library. The ”rotate” function is found to be the bottleneck in it. It must be implemented many times because of the FHE algorithm which cannot compare a ciphertext to another one. Finally, the compatibility of this application using the HElib library with SSDs is determined.