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GPU-Acceleration of Block Ciphers in the OpenSSL Cryptographic Library

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Information Security (ISC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7483))

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Abstract

The processing power of graphic processing units (GPUs) has been applied for cryptographic algorithms for some time. For AES and DES especially, there is large body of existing academic work and some available code which makes use of the CUDA framework.

We contribute to the field of symmetric-key GPU cryptography by implementing and benchmarking multiple block ciphers on CUDA and OpenCL in the form of an OpenSSL cryptographic engine. We show common techniques to implement and accelerate these block ciphers (AES, DES, Blowfish, Camellia, CAST5, IDEA). Another equally important part of our work presents a guideline on how to perform reproducible benchmarks of these ciphers and similar GPU algorithms.

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Author information

Authors and Affiliations

  1. Research Group IT-Security, RWTH Aachen University, Aachen, Germany

    Johannes Gilger, Johannes Barnickel & Ulrike Meyer

Authors
  1. Johannes Gilger
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  2. Johannes Barnickel
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  3. Ulrike Meyer
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Editor information

Editors and Affiliations

  1. Institute of Security in Distributed Applications, University of Technology, Harburger Schlossstrasse 20, 21073, Hamburg, Germany

    Dieter Gollmann

  2. Department of Computer Science, University of Erlangen-Nürnberg, Am Wolfsmantel 46, 91058, Erlangen, Germany

    Felix C. Freiling

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© 2012 Springer-Verlag Berlin Heidelberg

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Gilger, J., Barnickel, J., Meyer, U. (2012). GPU-Acceleration of Block Ciphers in the OpenSSL Cryptographic Library. In: Gollmann, D., Freiling, F.C. (eds) Information Security. ISC 2012. Lecture Notes in Computer Science, vol 7483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33383-5_21

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  • DOI: https://doi.org/10.1007/978-3-642-33383-5_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33382-8

  • Online ISBN: 978-3-642-33383-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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