4.7 Article

Image encryption algorithm based on a 2D-CLSS hyperchaotic map using simultaneous permutation and diffusion

期刊

INFORMATION SCIENCES
卷 605, 期 -, 页码 71-85

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2022.05.032

关键词

2D hyperchaotic map; Image encryption; Simultaneous permutation and diffusion; Security analysis

资金

  1. Postdoctoral Research Foundation of China [2020M680933]
  2. National Natural Science Foundation of China [61701070, 61672124]
  3. Doctoral Start-up Foundation of Liaoning Province [2018540090]
  4. Key R&D Projects of Liaoning Province [2019020105-JH2/103]
  5. Liaoning Province Science and Technology Innovation Leading Talents Program Project [XLYC1802013]
  6. Research Fund of Guangxi Key Lab of Multi-source Information Mining Security [MIMS20-M-02]
  7. Jinan City `20 universities' Funding Projects Introducing Innovation Team Program [2019GXRC031]

向作者/读者索取更多资源

A two-dimensional cross-mode hyperchaotic map based on logistic and sine maps is proposed in this paper. The chaotic behavior and performance of the system are analyzed, showing that it possesses promising ergodicity and a wide range of hyperchaotic phenomena. An effective image encryption algorithm is developed using this map.
A two-dimensional cross-mode hyperchaotic map based on logistic and sine maps (2DCLSS) is presented. The hyperchaotic map consists of a logistic map and two sine maps with cross structure. The chaotic behavior of the system is analyzed using bifurcation diagrams, Lyapunov exponential spectra, phase diagrams, etc. The outcomes demonstrate that the system has promising ergodicity and a wide range of hyperchaotic phenomena. Using the proposed 2D-CLSS, an image cryptography algorithm is developed. This image encryption system employs a strategy that simultaneously combines permutation and diffusion to alter the location and the value of the pixels. Experiments and security simulations indicate that the scheme is effective in encrypting images with excellent security against various attacks (differential, noise and data loss, etc.). (C) 2022 Elsevier Inc. All rights reserved.

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