基于串联结构的混沌序列

Serial-fabric chaotic spread-spectrum sequence

针对一般单峰映射混沌扩频序列的保密性差,易受攻击的缺点,本文提出了基于串联结构的混沌扩频序列,其产生的方法是用一个混沌系统的输出,作为另一个混沌系统的初始值.这样做的好处在于:两个混沌系统都是单峰映射混沌,便于数字实现;由于第二个混沌系统的初始值在不断的变化.可以有效的防止破译提高了保密性.在建立数学模型分析了其相关性和保密性的基础上,利用模糊神经网络对单峰映射的混沌序列与本文的混沌序列做了攻击(预测),验证了此方法的有效性.

Unimodel chaotic spread-spectrum sequence is easy to be attacked for its poor secrecy, a serial-fabric chaotic spread-spectrum sequence is therefore established by using the output of one chaotic system as the initial condition for another chaotic systems. These two chaotic systems are both ummodel maps and they are therefore easy for digital realization, and the initial value of the second chaotic system is changing all the time thereby improving its secrecy- The analysis of correlation property and secrecy with a mathematic model established ,and the attack of the chaotic sequence proposed in this paper and the unimodel chaotic sequence by the tuzzy neural network proved the effectiveness of thsi method.