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Bit-level color image encryption algorithm based on coarse-grained logistic map and fractional chaos

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Abstract

A novel color image encryption algorithm based on coarse-grained fractional chaotic system signals is proposed in this paper. First, color images are divided into three channels, which are encrypted based on the corresponding three states of the chaotic system. Second, the chaotic systems are defined as fractional chaotic, in which the fractional order enlarges the parameter space. Third, the fractional chaotic signals are handled with unfixed coarse-grained methods instead of being utilized directly. In addition, the original image and the chaotic signals are divided into bit signals from the pixel values, and the high and low bits are encrypted, respectively. To demonstrate the effectiveness and robustness of the proposed color image encryption algorithm, its properties, including the key space, information entropy, correlation analysis, key sensitivity, and resistance to differential attacks, are provided using a numerical simulation.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (Nos: 61702356, 61672124, 61503375 and 61701070), the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (No: MMJJ20170203).

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Authors and Affiliations

  1. School of Computer Science & Technology, BeiJing Institute of Technology, Beijing, 100081, China

    Yu-jie Sun

  2. College of Information & Computer, Taiyuan University of Technology, Taiyuan, 030024, China

    Hao Zhang

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, 116026, China

    Xing-yuan Wang

  4. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China

    Ming-xu Wang

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  1. Yu-jie Sun
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  2. Hao Zhang
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  3. Xing-yuan Wang
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  4. Ming-xu Wang
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Correspondence to Hao Zhang.

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Sun, Yj., Zhang, H., Wang, Xy. et al. Bit-level color image encryption algorithm based on coarse-grained logistic map and fractional chaos. Multimed Tools Appl 80, 12155–12173 (2021). https://doi.org/10.1007/s11042-020-10373-y

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  • DOI: https://doi.org/10.1007/s11042-020-10373-y

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