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A novel Hash algorithm construction based on chaotic neural network

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Abstract

An algorithm for constructing a one-way novel Hash function based on two-layer chaotic neural network structure is proposed. The piecewise linear chaotic map (PWLCM) is utilized as transfer function, and the 4-dimensional and one-way coupled map lattices (4D OWCML) is employed as key generator of the chaotic neural network. Theoretical analysis and computer simulation indicate that the proposed algorithm presents several interesting features, such as high message and key sensitivity, good statistical properties, collision resistance and secure against meet-in-the-middle attacks, which can satisfy the performance requirements of Hash function.

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Acknowledgments

Our sincere thanks go to the anonymous reviewers for their valuable comments. The work described in this paper was fully funded by Project No. CDJZR10180003 supported by the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. College of Computer Science, Chongqing University, 400044, Chongqing, China

    Yantao Li, Shaojiang Deng & Di Xiao

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  1. Yantao Li
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  2. Shaojiang Deng
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  3. Di Xiao
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Correspondence to Yantao Li.

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Li, Y., Deng, S. & Xiao, D. A novel Hash algorithm construction based on chaotic neural network. Neural Comput & Applic 20, 133–141 (2011). https://doi.org/10.1007/s00521-010-0432-2

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  • DOI: https://doi.org/10.1007/s00521-010-0432-2

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