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A novel image encryption algorithm using PWLCM map-based CML chaotic system and dynamic DNA encryption

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Abstract

A novel image encryption scheme based on deoxyribonucleic acid (DNA) is proposed utilizing the hash function and coupled map lattices (CML) based on the piecewise linear chaotic map (PWLCM) in this paper. First, the chaotic sequences for the entire encryption process are generated by the PWLCM map-based CML chaotic system, and the external keys and hash value of the plain image are employed to calculate the control parameters and initial values of the CML system and PWLCM map. Especially the f(x) sequences generated by PWLCM map are used many times. Second, in accordance with the chaotic sequences produced by CML and PWLCM map, the encryption process is divided into three modules. Module one is to implement pixel-level encryption through sort function and exclusive OR (XOR) operation. Then, the DNA encoding and decoding rules are dynamic selected by chaotic sequences. DNA-level encryption is carried out in module two by cyclic shift function and dynamic DNA permutation rules. Finally, a second diffusion encryption at pixel level is performed in module three through XOR operation to further enhance the utilization of chaotic sequences and security of the image encryption system. The results of experiment and security analyses have certified that the proposed scheme has an outstanding property and can withstand a variety of typical attacks.

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Acknowledgements

This work is supported by grants from National Basic Research Program of China [grant number 2019YFE0126600], National Natural Science Foundation of China [grant numbers U1704122] and Key Research and Promotion Projects of Henan Province [grant numbers 192102210096, 202102110121, 202102210368] and Kaifeng science and technology development plan [grant number 2002001].

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Correspondence to Sujuan Fan.

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Tian, J., Lu, Y., Zuo, X. et al. A novel image encryption algorithm using PWLCM map-based CML chaotic system and dynamic DNA encryption. Multimed Tools Appl 80, 32841–32861 (2021). https://doi.org/10.1007/s11042-021-11218-y

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