基于五阶CNN超混沌系统的图像加密方法  

Image Encryption Method Based on Fifth Order CNN Hyperchaotic System

作　　者：田佳鹭 邓立国 TIAN Jialu;DENG Liguo(School of Mathematics and Systems Science,Shenyang Normal University,Shenyang 110034 China)

机构地区：[1]沈阳师范大学数学与系统科学学院,辽宁沈阳110034

出　　处：《西华大学学报（自然科学版）》2021年第2期63-70,81,共9页Journal of Xihua University:Natural Science Edition

基　　金：辽宁省教育科学规划课题“教育信息化云生态环境的架构大数据研究”(JG16DB395)。

摘　　要：为提高二维图像加密的效果,提出一种将像素置乱和像素替换相结合的图像加密方法。首先,利用位平面分解处理明文图像,接着利用幻方变换置乱方法分别对8个位平面进行像素置乱加密预处理,然后对4个高位平面使用五阶细胞神经网络(CNN)超混沌系统产生的超混沌序列进行像素替换的再次加密。实验结果表明:加密后图像的信息熵可达到7.986,体现出较高的随机性;实现了对加密图像直方图的改变,降低了像素间的关联性。该方法有效地提高了二维图像的加密效果和抗攻击能力。In order to improve the effect of two-dimensional image encryption,the pixel scrambling and pixel are proposed to replace a combination of two methods to realize image encryption.In the first place,by using the bit-plane decomposition,the plaintext image was processed,and then the pixel scrambling encryption was preprocessed for the eight bit planes respectively by using the magic square transform scrambling method,and then the hyperchaotic sequence generated by the fifth-order cellular neural network(CNN)hyperchaotic system was used to encrypt the pixel replacement of the four higher level planes,and the algorithm of information entropy can reach 7.986.This embodied the high randomness.At the same time,the method can change the histogram of encrypted image and reduce the correlation between pixels,which can effectively improve the encryption effect and anti-attack ability of two-dimensional image.

关 键 词：图像加密 细胞神经网络 超混沌系统 幻方变换 位平面分解 

分 类 号：TP309.7[自动化与计算机技术—计算机系统结构] O415.5[自动化与计算机技术—计算机科学与技术]