基于神经网络的混沌加密算法

首先用神经网络来训练已知混沌序列，并利用该模型产生的非线性序列实现了明文、密文之间的转换，该算法的优点之一是神经网络（NN）隐式混沌映射关系使直接获取映射关系变得困难，经理论分析选择了较好的神经网络学习方法，实验进一步表明，该算法产生的序列随机性、抗破译性能良好；加密弹性大，可扩展性好；加密速度快。

A CHAOS ENCRYPTION ALGORITHM BASED ON NEURAL NETWORK

A better chaos sequence is generated by NN (neural network) through training the known nonlinear sequence. Then the sequence is used for mapping the plaintext to the cipher text. One advantage of the algorithm is that the hidden-mapping model of NN makes it difficult to get the direct mapping function of the ordinary chaos encryption algorithm. A better NN training method is achieved through theoretical analysis. Further more, the experiment shows that the output sequence has good random property as well as wonderful ability against decryption. From the practical point of view, the algorithm can be easily generalized to different ways by choosing the various known nonlinear sequences. The encryption speed of the algorithm is fast.