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    A new class of efficient piecewise nonlinear chaotic maps for secure cryptosystems

    133832_133832.pdf (262.1Kb)
    Access Status
    Open access
    Authors
    Li, Y.
    Feng, Q.
    Liu, Wan-quan
    Wang, Y.
    Date
    2009
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Li, Y. and Feng, Q. and Liu, Wan-quan and Wang, Y. 2009. A new class of efficient piecewise nonlinear chaotic maps for secure cryptosystems, in Lai, L. L. (ed), ICMLC 2009, Jul 12 2009, pp. 333-338.Baoding, Hebei, China: IEEE.
    Source Title
    Proceedings of the 8th International conference on Machine learning and Cybernetics
    Source Conference
    ICMLC 2009
    Additional URLs
    http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5212550
    ISBN
    9781424437030
    Faculty
    School of Science and Computing
    Department of Computing
    Faculty of Science and Engineering
    Remarks

    Copyright © 2009 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/14433
    Collection
    • Curtin Research Publications
    Abstract

    In this paper we construct a new class of nonlinear chaotic maps for secure cryptosystems. These maps can overcome the security holes brought by the "piecewise linearity" of the previous Piecewise Linear Chaotic Maps (PWLCM) due to a fact that the chaotic sequences generated by the derived iterative system based on the proposed maps are proved to have perfect dynamic properties, such as uniform invariant distribution, d-like autocorrelation function etc. Furthermore, the relative quantized two-value sequences also have perfect secure statistical characteristics. In terms of computing speed, the proposed maps have faster speed than the recently proposed nonlinear "piecewise-square-root" maps (PSRM), and they actually have equivalently the same computing speed with the linear PWLCM.

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