混沌映射和神经网络互扰的新型复合流密码

提出了一种将新型的神经网络互学习模型和常见的多混沌系统融合互扰的复合流密码方案. 首先利用三个Logistics混沌映射产生的随机序列作为神经网络互学习模型中三个 隐含层神经元的随机输入, 神经网络交互学习达到内部权值同步后, 再将同步权值映射为随机序列并与三个Logistics序列复合产生最终的密钥流. 实验表明, 产生的密钥流具有更好的随机性, 混沌流加密应用效果好.关键词：混沌映射神经网络权值同步随机密钥流

New hybrid stream cipher based on chaos and neural networks

A hybrid stream cipher scheme is proposed based on the novel interacting neural networks and the multiple chaotic systems. At first, random sequences generated by 3 independent logistics functions respectively are taken as dynamic inputs to 3 hidden layers of the interacting neural networks model. Then two inner weights of the two structures of neural networks will be synchronized through some steps of interacting learning, and the random key stream can be finally identified by combining the random sequence extracted from the aforementioned synchronized weight and 3 Logistics sequences. The comparison shows that the generated key stream performs the better randomness than others. As a good example, the proposed novel chaos-based stream cipher works perfectly on digital image encryption.