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A robustness-improved image encryption scheme utilizing Life-liked cellular automaton

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Abstract

Image encryption is considered as an effective method to protect image against revealing. As a discrete dynamic system, the Life-liked cellular automaton (CA) has good chaotic performance and has been applied for image encryption. This paper proposes a robust block encryption scheme, based on reversible Life-liked CA with balanced rule. The proposed method adopts classic confusion–diffusion structure on block level and reversible Life-liked CA within block. An effect permutation method is developed to reduce the iteration rounds of whole system, while the diffusion module adopts reversible Life-liked CA with balanced rule to encrypt the blocks to noise-like ones. Performance analyses show the proposed scheme have good cryptographic features, satisfactory security for defeating common attacks and robustness to resist data loss and random noise.

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Data availability

In this paper, the original plain images are from the USC-SIPI Image Database. We mainly use the images with size of 512 \(\times \) 512. And the database is available in https://sipi.usc.edu/database/. The proposed encryption scheme and some related analysis are implemented in C++, and some other tests, like the simulation of RCA, are implemented in MATLAB 2016a. These source code are open and can be found in: https://github.com/NEUboy/encode_RCA.git.

Notes

  1. https://sipi.usc.edu/database/.

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Acknowledgements

This work is funded by the National Natural Science Foundation of China (No. 62171114), the Fundamental Research Funds for the Central Universities (No. N2224001-7) and the National Key R &D Program of China (No. 2021YFF0306405).

Funding

This work is supported by the National Natural Science Foundation of China (No. 62171114), the Fundamental Research Funds for the Central Universities (No. N2224001-7) and the National Key R &D Program of China (No. 2021YFF0306405).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Wenrui Lv & Chong Fu

  2. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110819, China

    Junxin Chen

  3. School of Artificial Intelligence, Henan University, Zhengzhou, 450046, China

    Xiuli Chai

  4. Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Shenyang, China

    Chong Fu

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  1. Wenrui Lv
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  2. Junxin Chen
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Correspondence to Chong Fu.

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Lv, W., Chen, J., Chai, X. et al. A robustness-improved image encryption scheme utilizing Life-liked cellular automaton. Nonlinear Dyn 111, 3887–3907 (2023). https://doi.org/10.1007/s11071-022-08021-1

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