论文标题
基于混乱的对数图和密钥生成的图像加密方案使用深CNN
An Image Encryption Scheme Based on Chaotic Logarithmic Map and Key Generation using Deep CNN
论文作者
论文摘要
本研究提出了安全可靠的图像加密方案。加密方案在此引入了一个新颖的混沌日志图,密钥生成深度卷积神经网络(CNN)模型,以及用于操纵过程的位回归操作。多亏了敏感的密钥生成,为高差日映射产生了初始值和控制参数,因此可以为加密操作实现多种混乱序列。然后,该方案通过四个操作通过四个操作(置换,DNA编码,扩散和位归还)来加密图像来加密图像。通过各种分析(例如,钥匙敏感性,信息熵,直方图,相关性,差异攻击,嘈杂的攻击和种植攻击),精确检查了众所周知的图像的加密方案。为了证实该方案,甚至将视觉和数值结果与艺术状态的可用结果进行了比较。因此,通过优越的绝对和比较结果成功验证和验证了所提出的基于日志图的图像加密方案。
A secure and reliable image encryption scheme is presented in this study. The encryption scheme hereby introduces a novel chaotic log-map, deep convolution neural network (CNN) model for key generation, and bit reversion operation for the manipulation process. Thanks to the sensitive key generation, initial values and control parameters are produced for the hyperchaotic log-map, and thus a diverse chaotic sequence is achieved for encrypting operations. The scheme then encrypts the images by scrambling and manipulating the pixels of images through four operations: permutation, DNA encoding, diffusion, and bit reversion. The encryption scheme is precisely examined for the well-known images in terms of various analyses such as keyspace, key sensitivity, information entropy, histogram, correlation, differential attack, noisy attack, and cropping attack. To corroborate the scheme, the visual and numerical results are even compared with available outcomes of the state of the art. Therefore, the proposed log-map based image encryption scheme is successfully verified and validated by the superior absolute and comparative results.