A novel exponential one-dimensional chaotic map enhancer and its application in an image encryption scheme using modified ZigZag transform

Li, Donghan; Li, Jinqing; Di, Xiaoqiang

doi:10.1016/j.jisa.2022.103304

Cited by 9 publications

(1 citation statement)

References 57 publications

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“…Hua et al [ 14 ] coupled two one-dimensional chaotic maps by cosine transform and constructed a one-dimensional cosine chaotic map intensifier. Li et al [ 15 ] built a one-dimensional exponential chaotic map enhancer, increased the input chaotic map’s randomness, and added exponential components to the chaotic system structure. Hu et al [ 16 ] designed a new chaos model UCS, which improved the statistical properties of existing maps and expanded the parameter range by concatenating two 1D chaotic maps and performing modular operations.…”

Section: Introductionmentioning

confidence: 99%

An n-Dimensional Chaotic Map with Application in Reversible Data Hiding for Medical Images

Yang,

Chang,

Feng

et al. 2024

Entropy

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The drawbacks of a one-dimensional chaotic map are its straightforward structure, abrupt intervals, and ease of signal prediction. Richer performance and a more complicated structure are required for multidimensional chaotic mapping. To address the shortcomings of current chaotic systems, an n-dimensional cosine-transform-based chaotic system (nD-CTBCS) with a chaotic coupling model is suggested in this study. To create chaotic maps of any desired dimension, nD-CTBCS can take advantage of already-existing 1D chaotic maps as seed chaotic maps. Three two-dimensional chaotic maps are provided as examples to illustrate the impact. The findings of the evaluation and experiments demonstrate that the newly created chaotic maps function better, have broader chaotic intervals, and display hyperchaotic behavior. To further demonstrate the practicability of nD-CTBCS, a reversible data hiding scheme is proposed for the secure communication of medical images. The experimental results show that the proposed method has higher security than the existing methods.

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Section: Introductionmentioning

confidence: 99%