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基于扰动数字混沌的图像置换与扩散新模型

Novel Models of Image Permutation and Diffusion Based on Perturbed Digital Chaos.

作者信息

Hoang Thang Manh, Assad Safwan El

机构信息

School of Electronics and Telecommunications, Hanoi University of Science and Technology, 1 Dai Co Viet, Hai Ba Trung, Hanoi 100000, Vietnam.

IETR (Institut d'Electronique et des Télécommunications de Rennes), Université de Nantes, CNRS, UMR 6164, Polytech Nantes, Rue Christian Pauc CS 50609, CEDEX 3, 44306 Nantes, France.

出版信息

Entropy (Basel). 2020 May 13;22(5):548. doi: 10.3390/e22050548.

Abstract

Most of chaos-based cryptosystems utilize stationary dynamics of chaos for the permutation and diffusion, and many of those are successfully attacked. In this paper, novel models of the image permutation and diffusion are proposed, in which chaotic map is perturbed at bit level on state variables, on control parameters or on both. Amounts of perturbation are initially the coordinate of pixels in the permutation, the value of ciphered word in the diffusion, and then a value extracted from state variables in every iteration. Under the persistent perturbation, dynamics of chaotic map is nonstationary and dependent on the image content. The simulation results and analyses demonstrate the effectiveness of the proposed models by means of the good statistical properties of transformed image obtained after just only a single round.

摘要

大多数基于混沌的密码系统利用混沌的平稳动力学进行置换和扩散,其中许多已被成功攻击。本文提出了新颖的图像置换和扩散模型,其中混沌映射在状态变量、控制参数或两者上进行比特级扰动。扰动幅度最初是置换中像素的坐标、扩散中密文的值,然后是每次迭代中从状态变量提取的值。在持续扰动下,混沌映射的动力学是非平稳的且依赖于图像内容。仿真结果和分析通过仅一轮变换后获得的变换图像的良好统计特性证明了所提模型的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ffe/7517044/5d44bcc9ac39/entropy-22-00548-g001.jpg

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