FPGA-based hardware accelerator for leveled RIng-LWE fully homomorphic encryption

Abstract

Fully homomorphic encryption (FHE) allows arbitrary computation on encrypted data and has great potential in privacy-preserving cloud computing and securely outsource computational tasks. However, the excessive computation complexity is the key limitation that restricting the practical application of FHE. In this paper we proposed a FPGA-based high parallelism architecture to accelerate the FHE schemes based on the ring learning with errors (RLWE) problem, specifically, we presented a fast implementation of leveled fully homomorphic encryption scheme BGV. In order to reduce the computation latency and improve the performance, we applied both circuit-level and block-level pipeline strategies to improve clock frequency, and as a result, enhance the processing speed of polynomial multipliers and homomorphic evaluation functions. At the same time, multiple polynomial multipliers and modular reduction units were deployed in parallel to further improve the hardware performance. Finally, we implemented and tested our architecture on a Virtex UltraScale FPGA platform. Runing at 150MHz, our implementation achieved 4.60×∼9.49× speedup with respect to the optimized software implementation on Intel i7 processor running at 3.1GHz for homomorphic encryption and decryption, and the throughput was increased by 1.03×∼4.64× compared to the hardware implementation of BGV. While compared to the hardware implementation of FV, the throughput of our accelerator also achieved 5.05× and 167.3× speedup for homomorphic addition and homomorphic multiplication operation respectively.