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Combining RBF Neural Network and Chaotic Map to Construct Hash Function

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Book cover Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

How to design an efficient and security keyed hash function is always the point in modern cryptography researches. In this paper, A better chaos sequence is generated by RBF neural network through training the known chaotic sequence generated by a piecewise nonlinear map, then the sequence is used to construct keyed hash function. One advantage of the algorithm is that the hidden-mapping model of neural network makes it difficult to get the direct mapping function of the ordinary chaos hash algorithm. Simulation results show that the keyed hash function based on the neural network has good one-way, weak collision, better security property and it can be realized easily.

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References

  1. Schneier, B.: Applied Cryptography, 3rd edn. China Machine Press, Beijing (2001)

    Google Scholar 

  2. Pieprzyh, J.: Design of Hashing Algorithm. Springer, Heidelberg (1993)

    Google Scholar 

  3. Xiaomin, W., Jianhu, Z., Wenfang, Z.: One Way Hash Function Construction Based on the Extended Chaotic Maps Switch. Acta Physica Sinica 52(6), 273–275 (2003)

    Google Scholar 

  4. Junning, L., Jiecheng, X., Pu, W.: One Way Hash Function Construction Based on Chaotic Mappings. J Tsinghua Univ. 40(3), 55–58 (2000)

    Google Scholar 

  5. Hongda, L., Dengguo, F.: Composite Nonlinear Discrete Chaotic Dynamical Systems and Keyed Hash Functions. Chinese Journal of Computers 26(5), 460–465 (2003)

    Google Scholar 

  6. Tao, S., Ruli, W., Yixun, Y.: Generating Binary Bernoulli Sequences Based on a Class of Even-Symmetric Chaotic Maps. IEEE Tran. Communications 49(8), 620–623 (2001)

    MATH  Google Scholar 

  7. Guojie, H., Zhengjin, F.: Theoretical Design for a Class of New Chaotic Stream Cipher. Communications Technology 24(4), 73–74 (2003)

    Google Scholar 

  8. Di, X., Xiaofeng, L.: A Combined Hash and Encryption Scheme by Chaotic Neural Network. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3174, pp. 633–638. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  9. Di, X., Xiaofeng, L., Guoping, T., Chuandong, L.: Using Chebyshev Chaotic Map to Construct Infinite Length Hash Chains. In: 2004 International Conference on Communications Circuits and Systems, pp. 11–12 (2004)

    Google Scholar 

  10. Kwok-Wo, W.: A Combined Chaotic Cryptographic and Hashing Scheme. Physics Letters A 307(10), 292–298 (2003)

    MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Chongqing University, 400044, China

    Pengcheng Wei, Wei Zhang & Huaqian Yang

  2. Department of Computer and Modern Education Technology, Chongqing Education College, Chongqing, 400067, China

    Pengcheng Wei, Wei Zhang, Huaqian Yang & Jun Chen

Authors
  1. Pengcheng Wei
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  2. Wei Zhang
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  3. Huaqian Yang
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  4. Jun Chen
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Wei, P., Zhang, W., Yang, H., Chen, J. (2006). Combining RBF Neural Network and Chaotic Map to Construct Hash Function. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_49

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  • DOI: https://doi.org/10.1007/11760191_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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