Color Image Encryption Based on Deep Learning and Block Embedding
Yi Liu, Gang Cen, Bijun Xu, Xiaogang Wang
Abstract
Because of the advent of the information age, digital multimedia data are mainly transmitted through the Internet. Image is one of the most popular digital multimedia data. Therefore, this paper proposes a block-based key embedding method and a color image encryption scheme based on deep learning with this method. By using a neural network model to predict the initial chaotic sequence, the key data generated by prediction are encrypted to the color image in layers and blocks. This paper proposed the color image encryption scheme time complexity <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>O</a:mi> <a:mfenced open="(" close=")" separators="|"> <a:mrow> <a:msup> <a:mrow> <a:mi>n</a:mi> </a:mrow> <a:mrow> <a:mn>2</a:mn> </a:mrow> </a:msup> </a:mrow> </a:mfenced> </a:math> , which is simple and effective. Simulation results show that the proposed scheme exhibits good statistical properties with information entropy mean close to eight and correlation coefficient close to zero. Good robustness to common image attacks like noise addition and cropping. Excellent encryption performance includes enormous key space and low PSNR.