Speeding up homomorpic hashing using GPUs

Kaiyong Zhao*, Xiaowen CHU, Mea Wang, Yixin Jiang

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

12 Citations (Scopus)


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 proposes 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.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Communications, ICC 2009
Publication statusPublished - 2009
Event2009 IEEE International Conference on Communications, ICC 2009 - Dresden, Germany
Duration: 14 Jun 200918 Jun 2009

Publication series

NameIEEE International Conference on Communications
ISSN (Print)0536-1486


Conference2009 IEEE International Conference on Communications, ICC 2009

Scopus Subject Areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

User-Defined Keywords

  • CUDA
  • GPU computing
  • Homomorphic hash function


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