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International Conference on Parallel Problem Solving from Nature

PPSN 2014: Parallel Problem Solving from Nature – PPSN XIII pp 414–423Cite as

Bent Function Synthesis by Means of Cartesian Genetic Programming

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8672))

Abstract

In this paper, a new approach to synthesize bent Boolean functions by means of Cartesian Genetic Programming (CGP) is proposed. Bent functions have important applications in cryptography due to their high nonlinearity. However, they are very rare and their discovery using conventional brute force methods is not efficient enough. We show that by using CGP we can routinely design bent functions of up to 16 variables. The evolutionary approach exploits parallelism in both the fitness calculation and the search algorithm.

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, Brno University of Technology, Bozetechova 2, 61266, Brno, Czech republic

    Radek Hrbacek & Vaclav Dvorak

Authors
  1. Radek Hrbacek
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  2. Vaclav Dvorak
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Editor information

Editors and Affiliations

  1. Faculty of Computer and Engineering Sciences, Cologne University of Applied Sciences, Steinmüllerallee 1, 51643, Gummersbach, Germany

    Thomas Bartz-Beielstein

  2. Warwick Business School, University of Warwick, CV8 2SY, Coventry, UK

    Jürgen Branke

  3. Department of Intelligent Systems, JožefStefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia

    Bogdan Filipič

  4. Department of Computer Science and Creative Technologies, University of the West of England, BS16 1QY, Bristol, UK

    Jim Smith

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© 2014 Springer International Publishing Switzerland

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Hrbacek, R., Dvorak, V. (2014). Bent Function Synthesis by Means of Cartesian Genetic Programming. In: Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (eds) Parallel Problem Solving from Nature – PPSN XIII. PPSN 2014. Lecture Notes in Computer Science, vol 8672. Springer, Cham. https://doi.org/10.1007/978-3-319-10762-2_41

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  • DOI: https://doi.org/10.1007/978-3-319-10762-2_41

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10761-5

  • Online ISBN: 978-3-319-10762-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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