International Conference on Financial Cryptography and Data Security

FC 2015: Financial Cryptography and Data Security pp 160-171 | Cite as

Accelerating SWHE Based PIRs Using GPUs

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8976)

Abstract

In this work we focus on tailoring and optimizing the computational Private Information Retrieval (cPIR) scheme proposed in WAHC 2014 for efficient execution on graphics processing units (GPUs). Exploiting the mass parallelism in GPUs is a commonly used approach in speeding up cPIRs. Our goal is to eliminate the efficiency bottleneck of the Doröz et al. construction which would allow us to take advantage of its excellent bandwidth performance. To this end, we develop custom code to support polynomial ring operations and extend them to realize the evaluation functions in an optimized manner on high end GPUs. Specifically, we develop optimized CUDA code to support large degree/large coefficient polynomial arithmetic operations such as modular multiplication/reduction, and modulus switching. Moreover, we choose same prime numbers for both the CRT domain representation of the polynomials and for the modulus switching implementation of the somewhat homomorphic encryption scheme. This allows us to combine two arithmetic domains, which reduces the number of domain conversions and permits us to perform faster arithmetic. Our implementation achieves 14–34 times speedup for index comparison and 4–18 times speedup for data aggregation compared to a pure CPU software implementation.

Keywords

Private information retrieval Homomorphic encryption NTRU 

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Copyright information

© International Financial Cryptography Association 2015

Authors and Affiliations

  1. 1.Worcester Polytechnic InstituteWorcesterUSA

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