An Image Encryption Scheme Based on Chaotic Logarithmic Map and Key Generation using Deep CNN

by   Uğur Erkan, et al.

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.



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An Image Encryption Scheme Based on Chaotic Logarithmic Map and Key Generation using Deep CNN

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