中国物理B ›› 2008, Vol. 17 ›› Issue (7): 2388-2393.doi: 10.1088/1674-1056/17/7/011

• GENERAL • 上一篇    下一篇

One-way hash function based on hyper-chaotic cellular neural network

杨群亭, 高铁杠   

  1. College of Software, Nankai University, Tianjin 300071, China
  • 收稿日期:2007-11-22 修回日期:2007-12-31 出版日期:2008-07-09 发布日期:2008-07-09
  • 基金资助:
    Project supported by Key Program of Natural Science Fund of Tianjin of China (Grant No 07JCZDJC06600).

One-way hash function based on hyper-chaotic cellular neural network

Yang Qun-Ting(杨群亭) and Gao Tie-Gang(高铁杠)†   

  1. College of Software, Nankai University, Tianjin 300071, China
  • Received:2007-11-22 Revised:2007-12-31 Online:2008-07-09 Published:2008-07-09
  • Supported by:
    Project supported by Key Program of Natural Science Fund of Tianjin of China (Grant No 07JCZDJC06600).

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摘要： The design of an efficient one-way hash function with good performance is a hot spot in modern cryptography researches. In this paper, a hash function construction method based on cell neural network with hyper-chaos characteristics is proposed. First, the chaos sequence is gotten by iterating cellular neural network with Runge--Kutta algorithm, and then the chaos sequence is iterated with the message. The hash code is obtained through the corresponding transform of the latter chaos sequence. Simulation and analysis demonstrate that the new method has the merit of convenience, high sensitivity to initial values, good hash performance, especially the strong stability.

Abstract: The design of an efficient one-way hash function with good performance is a hot spot in modern cryptography researches. In this paper, a hash function construction method based on cell neural network with hyper-chaos characteristics is proposed. First, the chaos sequence is gotten by iterating cellular neural network with Runge--Kutta algorithm, and then the chaos sequence is iterated with the message. The hash code is obtained through the corresponding transform of the latter chaos sequence. Simulation and analysis demonstrate that the new method has the merit of convenience, high sensitivity to initial values, good hash performance, especially the strong stability.

Key words: one-way hash function, hyper-chaos, cellular neural network, Runge--Kutta formula

中图分类号:  (Quantum cryptography and communication security)

  • 03.67.Dd
05.45.Pq (Numerical simulations of chaotic systems) 07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)