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Accelerating SWHE Based PIRs Using GPUs

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Financial Cryptography and Data Security (FC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8976))

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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.

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Notes

  1. 1.

    The NVIDIA GeForce GTX 690 series actually consist of two GTX 680 series graphical processors.

  2. 2.

    In cases where we extract entries with more than 1-bit size, we use the same index comparison result to process the remaining bits of a database entry. Also timings that given on the table are per polynomial operation and they are not normalized.

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Acknowledgments

Funding for this research was in part provided by the US National Science Foundation CNS Award #1319130.

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Authors and Affiliations

  1. Worcester Polytechnic Institute, Worcester, USA

    Wei Dai, Yarkın Doröz & Berk Sunar

Authors
  1. Wei Dai
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  2. Yarkın Doröz
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  3. Berk Sunar
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Corresponding author

Correspondence to Wei Dai .

Editor information

Editors and Affiliations

  1. Leibniz Universität, Hannover, Germany

    Michael Brenner

  2. Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Nicolas Christin

  3. Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Benjamin Johnson

  4. New Jersey Institute of Technology, Newark, New Jersey, USA

    Kurt Rohloff

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© 2015 International Financial Cryptography Association

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Dai, W., Doröz, Y., Sunar, B. (2015). Accelerating SWHE Based PIRs Using GPUs. In: Brenner, M., Christin, N., Johnson, B., Rohloff, K. (eds) Financial Cryptography and Data Security. FC 2015. Lecture Notes in Computer Science(), vol 8976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48051-9_12

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  • DOI: https://doi.org/10.1007/978-3-662-48051-9_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48050-2

  • Online ISBN: 978-3-662-48051-9

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