4.7 Article

A fast and efficient multiple images encryption based on single-channel encryption and chaotic system

期刊

NONLINEAR DYNAMICS
卷 108, 期 1, 页码 613-636

出版社

SPRINGER
DOI: 10.1007/s11071-021-07192-7

关键词

Multiple images; Encryption; Single-channel; Chaotic system

资金

  1. National Natural Science Foundation of China [62061014]
  2. Natural Science Foundation of Liaoning Province [2020MS-274]
  3. Basic Scientific Research Projects of Colleges and Universities of Liaoning Province [LJKZ0545]

向作者/读者索取更多资源

This paper proposes a multiple-image encryption algorithm based on single-channel scrambling, diffusion, and chaotic system. The algorithm encrypts the image set by fusing and converting from the RGB channel to the HSV channel. For single-channel encryption, scrambling and diffusion operations are performed. The algorithm shows excellent encryption speed and security performance based on performance analysis.
A multiple-image encryption algorithm based on single-channel scrambling, diffusion and chaotic system is presented in this paper. The initial values of the chaotic system are associated with the pixel values of each set of encrypted images as the key for each set of image encryption. The pseudo-random sequences and matrixes generated by the chaotic system are obtained by the corresponding keys, and then, the whole set of images are fused across-image and transferred from the RGB channel to the HSV channel after fusion. For single-channel encryption, select one of the HSV channels is extracted and encryption operations of scrambling and diffusion are performed. The index sequences generated by the chaotic sequences with zero frequency shifting rearrange the pixel positions of the encrypted channel. Combining data splitting, stack storage, and chaotic matrixes, the diffusion operation is achieved. Analyses of the performance show that the algorithm has both excellent encryption speed and security performance.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据