Speeding Up Homomorpic Hashing Using GPUs

Abstract

Homomorphic hash functions (HHFs) have been applied into peer-to-peer networks with erasure coding or network coding to defend against pollution attacks. Unfortunately HHFs are computationally expensive for contemporary CPUs, This paper to exploit the computing power of graphic processing units (GPUs) for homomorphic hashing. Specifically, we demonstrate how to use NVIDIA GPUs and the computer unified device architecture (CUDA) programming model to achieve 38 times of speedup over the CPU counterpart. We also develop a multi-precision modular arithmetic library on CUDA platform, which is not only key to our specific application, but also very useful for a large number of cryptographic applications.