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A fast and efficient hash function based on generalized chaotic mapping with variable parameters

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Abstract

We present a fast and efficient hash algorithm based on a generalized chaotic mapping with variable parameters in this paper. We first define a generalized chaotic mapping by utilizing piecewise linear chaotic map and trigonometric functions. Then, we convert the arbitrary length of message into the corresponding ASCII values and perform 6-unit iterations with variable parameters and message values based on the generalized chaotic mapping. The final hash value is obtained by cascading extracted bits from iteration state values. We excessively evaluate the proposed algorithm in terms of distribution of hash value, sensitivity of hash value to the message and secret keys, statistical analysis of diffusion and confusion, analysis of birthday attacks and collision resistance, analysis of secret keys, analysis of speed, and comparison with other algorithms, and the results illustrate that the suggested algorithm is fast, efficient, and enough simple and has good confusion and diffusion capabilities, strong collision resistance, and a high level of security.

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Acknowledgments

Our sincere thanks go to the anonymous reviewers for their valuable comments. This work is supported in part by the National Natural Science Foundation of China (Grant Nos. 61402380 and 61528206), the Natural Science Foundation of CQ CSTC (Grant No. cstc2015jcyjA40044), and the Fundamental Research Funds for the Central Universities (Grant No. XDJK2015B030).

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Authors and Affiliations

  1. College of Computer and Information Sciences, Southwest University, Chongqing, 400715, China

    Yantao Li & Xiang Li

  2. College of Mathematics and Statistics, Chongqing University of Technology, Chongqing, 400054, China

    Xiangwei Liu

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  1. Yantao Li
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  2. Xiang Li
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  3. Xiangwei Liu
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Correspondence to Yantao Li.

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Li, Y., Li, X. & Liu, X. A fast and efficient hash function based on generalized chaotic mapping with variable parameters. Neural Comput & Applic 28, 1405–1415 (2017). https://doi.org/10.1007/s00521-015-2158-7

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  • DOI: https://doi.org/10.1007/s00521-015-2158-7

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