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Parallelization of Encryption Algorithm Based on Chaos System and Neural Networks

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Parallel Processing and Applied Mathematics (PPAM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8385))

Abstract

In this paper, the results of parallelizing of encryption algorithm based on a chaos system and neural networks are presented. A data dependence analysis of loops was applied in order to parallelize the algorithm. The parallelism of the algorithm is demonstrated in accordance with the OpenMP standard. As a result of my study, it was stated that the most time-consuming loops of the algorithm are suitable for parallelization. The efficiency measurement of a parallel program is showed.

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Authors and Affiliations

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

    Dariusz Burak

Authors
  1. Dariusz Burak
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Correspondence to Dariusz Burak .

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Editors and Affiliations

  1. Institute of Computer and Information Science, Czestochowa University of Technology, Czestochowa, Poland

    Roman Wyrzykowski

  2. University of Tennessee, Department of Computer Science, Knoxville, Tennessee, USA

    Jack Dongarra

  3. Institute of Computer and Information Science, Czestochowa University of Technology, Czestochowa, Poland

    Konrad Karczewski

  4. Technical University of Denmark Informatics and Mathematical Modelling, Kongens Lyngby, Denmark

    Jerzy Waśniewski

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Burak, D. (2014). Parallelization of Encryption Algorithm Based on Chaos System and Neural Networks. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2013. Lecture Notes in Computer Science(), vol 8385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55195-6_34

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  • DOI: https://doi.org/10.1007/978-3-642-55195-6_34

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55194-9

  • Online ISBN: 978-3-642-55195-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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