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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2015: Artificial Intelligence and Soft Computing pp 191–201Cite as

Parallelization of a Block Cipher Based on Chaotic Neural Networks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9120))

Abstract

In this paper the results of parallelizing a block cipher based on chaotic neural networks are presented. A data dependence analysis of loops is applied in order to parallelize the algorithm. The parallelism of the algorithm is demonstrated in accordance with the OpenMP standard. As a result of this study, it is stated that the most time-consuming loops of the algorithm are suitable for parallelization. The efficiency measurements of a parallel algorithm working in standard modes of operation are shown.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, 49 Żołnierska St., 71-210, Szczecin, Poland

    Dariusz Burak

Authors
  1. Dariusz Burak
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Corresponding author

Correspondence to Dariusz Burak .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Czestochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Czestochova Univ of Technology, Częstochova, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Burak, D. (2015). Parallelization of a Block Cipher Based on Chaotic Neural Networks. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_18

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  • DOI: https://doi.org/10.1007/978-3-319-19369-4_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19368-7

  • Online ISBN: 978-3-319-19369-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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