基于细胞神经网络超混沌特性的图像加密新算法

New image encryption algorithm based on cellular neural network

针对一般流密码对明文变化不敏感的缺陷,基于细胞神经网络(CNN),提出一种图像加密新算法。以一个6维CNN产生的超混沌系统作为密钥源,并根据明文图像各点像素值的逻辑运算结果选取密钥;同时使用像素位置置乱和像素值替代两种方法对数字图像进行加密。实验表明,该算法加密效果好,NPCR值和密钥敏感性高(>0.996),满足数字图像加密安全性的要求,同时具有计算简单、易于实现、能提高数字图像传输的安全性等特点。

In this paper,a new image encryption algorithm was presented by employing Cellular Neural Network（CNN）.The main objective was to solve the problem of traditional stream cipher＇s insensitivity to the change of plain text.By using a hyper chaotic system of 6-D CNN as the key source,selecting the secret key based on the results of logical operations of pixel values in the plain image,and introducing simultaneously both position permutation and value transformation,the new algorithm was presented.It is shown that both NPCR value and the sensitivity to key（0.996） can meet the security requirements of image encryption.The simulation process also indicates that the algorithm is relatively easy to realize with low computation complexity,and ensures,accordingly,the secure transmission of digital images.