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Security analysis of chaotic communication systems based on Volterra–Wiener–Korenberg model

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  • Lei, Min
  • Meng, Guang
  • Feng, Zhengjin

Abstract

Pseudo-randomicity is an important cryptological characteristic for proof of encryption algorithms. This paper proposes a nonlinear detecting method based on Volterra–Wiener–Korenberg model and suggests an autocorrelation function to analyze the pseudo-randomicity of chaotic secure systems under different sampling interval. The results show that: (1) the increase of the order of the chaotic transmitter will not necessarily result in a high degree of security; (2) chaotic secure systems have higher and stronger pseudo-randomicity at sparse sampling interval due to the similarity of chaotic time series to the noise; (3) Volterra–Wiener–Korenberg method can also give a further appropriate sparse sampling interval for improving the security of chaotic secure communication systems. For unmasking chaotic communication systems, the Volterra–Wiener–Korenberg technique can be applied to analyze the chaotic time series with surrogate data.

Suggested Citation

  • Lei, Min & Meng, Guang & Feng, Zhengjin, 2006. "Security analysis of chaotic communication systems based on Volterra–Wiener–Korenberg model," Chaos, Solitons & Fractals, Elsevier, vol. 28(1), pages 264-270.
    • Handle: RePEc:eee:chsofr:v:28:y:2006:i:1:p:264-270
    DOI: 10.1016/j.chaos.2005.05.040
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    References listed on IDEAS

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    Cited by:

    1. Zhang, Yu & Sprecher, Alicia J. & Zhao, ZongXi & Jiang, Jack J., 2011. "Nonlinear detection of disordered voice productions from short time series based on a Volterra–Wiener–Korenberg model," Chaos, Solitons & Fractals, Elsevier, vol. 44(9), pages 751-758.
    2. Yang, Jiyun & Liao, Xiaofeng & Yu, Wenwu & Wong, Kwok-wo & Wei, Jun, 2009. "Cryptanalysis of a cryptographic scheme based on delayed chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 40(2), pages 821-825.
    3. Zhang, Linhua, 2008. "Cryptanalysis of the public key encryption based on multiple chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 37(3), pages 669-674.
    4. Han, S. & Chang, E. & Dillon, T. & Hwang, M. & Lee, C., 2009. "Identifying attributes and insecurity of a public-channel key exchange protocol using chaos synchronization," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2569-2575.
    5. Lei, Min & Meng, Guang, 2008. "The influence of noise on nonlinear time series detection based on Volterra–Wiener–Korenberg model," Chaos, Solitons & Fractals, Elsevier, vol. 36(2), pages 512-516.
    6. Tang, Fang, 2008. "An adaptive synchronization strategy based on active control for demodulating message hidden in chaotic signals," Chaos, Solitons & Fractals, Elsevier, vol. 37(4), pages 1090-1096.
    7. Zaher, Ashraf A., 2009. "An improved chaos-based secure communication technique using a novel encryption function with an embedded cipher key," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 2804-2814.

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