基于混沌系统和人工神经网络的图像加密算法

针对一些基于混沌的图像加密算法中存在密钥与明文不相关, 混沌序列存在周期性等问题, 提出新的加密方案. 首先基于明文图像和哈希函数SHA-384产生Lorenz混沌系统的初值, 控制混沌系统产生混沌序列, 然后引入人工神经网络对混沌序列进行训练以消除其混沌周期性, 输出新的序列. 使用新的序列对明文图像进行置乱和扩散操作, 完成加密. 实验结果表明, 该算法提高了密文的安全性, 增大了密钥空间, 同时能抵抗各种攻击方式.

Image Encryption Algorithm Based on Chaotic System and Artificial Neural Network

In some chaos-based image encryption algorithms, the key is not related to the plaintext and the chaotic sequence has periodicity. In order to solve these problems, a new image encryption method is proposed. First, based on the plaintext image and the hash function SHA-384, the initial value of the Lorenz is generated, and the chaotic system is controlled to generate chaotic sequences. Then, the artificial neural network is introduced to train the chaotic sequence to eliminate its chaotic periodicity and output a new sequence. The scrambling and diffusion operations are performed on the plaintext image to complete the encryption. The experimental results show that the proposed algorithm is able to enhance the security of the cipher-image, increase the size of the key space and resist various attacks.