Chaotic image encryption algorithm based on fractal-chaotic dynamic S-box
This paper proposes an image encryption algorithm based on a fractal-chaotic dynamic S-box, aiming at the low flexibility of fractal-disordered matrix design, the complexity of iterative design, and the low information entropy and robustness of encrypted images caused by unreasonable S-box design. F...
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| Vydané v: | Nonlinear dynamics Ročník 113; číslo 17; s. 23613 - 23634 |
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| Jazyk: | English |
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Springer Nature B.V
01.09.2025
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| ISSN: | 0924-090X, 1573-269X |
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| Abstract | This paper proposes an image encryption algorithm based on a fractal-chaotic dynamic S-box, aiming at the low flexibility of fractal-disordered matrix design, the complexity of iterative design, and the low information entropy and robustness of encrypted images caused by unreasonable S-box design. Firstly, the 3D-coupled sine-Chebyshev chaotic system is controlled to generate chaotic sequences by the random matrix generator and KeyHex generation key, and the sequences for synchronous scrambling are generated by the 4D-hyperchaotic system, and the initial S-box is obtained by the fraction-Zigzags iteration of a simple initial matrix. Secondly, the chaotic sequence generated by 3D-coupled sine-Chebyshev mapping is used to disarrange the initialized S-box to obtain the fractal-chaotic dynamic S-box. Finally, by using the diffusion sequence generated by the 3D-coupled sine-Chebyshev chaotic system, the scrambling sequence generated by the 4D-hyperchaotic system and the fraction-chaotic dynamic S-box to carry out synchronous S-box replacement scrambling and diffusion operation for the image, Then the chaotic sequence generated by 3D-coupled sine-Chebyshev mapping is used to globally rearrange and diffuse the processed images to obtain ciphertext images. The experimental results show that the algorithm has high security and good robustness. |
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| AbstractList | This paper proposes an image encryption algorithm based on a fractal-chaotic dynamic S-box, aiming at the low flexibility of fractal-disordered matrix design, the complexity of iterative design, and the low information entropy and robustness of encrypted images caused by unreasonable S-box design. Firstly, the 3D-coupled sine-Chebyshev chaotic system is controlled to generate chaotic sequences by the random matrix generator and KeyHex generation key, and the sequences for synchronous scrambling are generated by the 4D-hyperchaotic system, and the initial S-box is obtained by the fraction-Zigzags iteration of a simple initial matrix. Secondly, the chaotic sequence generated by 3D-coupled sine-Chebyshev mapping is used to disarrange the initialized S-box to obtain the fractal-chaotic dynamic S-box. Finally, by using the diffusion sequence generated by the 3D-coupled sine-Chebyshev chaotic system, the scrambling sequence generated by the 4D-hyperchaotic system and the fraction-chaotic dynamic S-box to carry out synchronous S-box replacement scrambling and diffusion operation for the image, Then the chaotic sequence generated by 3D-coupled sine-Chebyshev mapping is used to globally rearrange and diffuse the processed images to obtain ciphertext images. The experimental results show that the algorithm has high security and good robustness. |
| Author | Ge, Bin Li, Weifeng |
| Author_xml | – sequence: 1 givenname: Bin surname: Ge fullname: Ge, Bin – sequence: 2 givenname: Weifeng surname: Li fullname: Li, Weifeng |
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| Cites_doi | 10.1007/s11071-024-10604-z 10.1016/j.matcom.2022.07.029 10.1016/j.matcom.2023.01.036 10.1109/JIOT.2023.3288678. 10.1109/TNNLS.2022.3146570 10.1016/j.sigpro.2018.10.011 10.1007/s11071-024-09870-8 10.1016/j.jisa.2024.103793 10.1007/s11071-024-09816-0 10.1016/j.jisa.2024.103723 10.1007/s11071-023-08578-5 10.3390/sym11030437 10.1016/j.jksuci.2023.101595 10.1016/j.eswa.2023.121514 10.1007/s11071-024-09966-1 10.1016/j.eswa.2023.120811 10.1016/j.jisa.2020.102699 10.1155/2021/3367521 10.1016/j.eswa.2024.123190 10.1007/s11071-024-10083-2 10.1016/j.eswa.2022.118924 10.1007/s11071-019-05311-z 10.1109/JIOT.2025.3540097 10.1016/j.matcom.2022.12.025 10.3390/math10173180 10.1109/TII.2024.3395631 10.1016/j.amc.2022.127738 10.1007/s11071-024-09632-6 10.1016/j.optlastec.2019.03.005 10.1016/j.eswa.2022.118845 10.1016/j.ins.2022.11.104 10.1016/j.chaos.2004.02.019 10.1016/j.ins.2021.01.014 10.1007/s11071-024-09644-2 10.1007/s11071-020-06098-0 10.1109/TCSVT.2022.3222559 10.1109/TCSVT.2021.3108767 10.1016/j.eswa.2022.119074 10.1007/s10489-023-04727-w 10.1016/j.optlastec.2022.109033 10.1007/s11071-024-09620-w 10.1063/5.0085031 10.1007/s11071-023-09010-8 10.1007/s11071-019-05413-8 10.1007/s11071-024-10268-9 10.1016/j.eswa.2024.125328 10.1016/j.eswa.2023.122779 10.1016/j.eswa.2023.122030 |
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| References | U Hayat (11367_CR27) 2019; 155 S Ibrahim (11367_CR26) 2021; 558 A Banik (11367_CR41) 2024 S Khan (11367_CR37) 2024; 112 P Liu (11367_CR1) 2023; 33 11367_CR29 S Zhou (11367_CR34) 2024; 112 J Tang (11367_CR35) 2024; 112 Y Xian (11367_CR20) 2022; 32 11367_CR2 11367_CR5 11367_CR4 11367_CR7 AH Zahid (11367_CR28) 2019; 11 11367_CR9 M Alawida (11367_CR46) 2019; 98 X Liu (11367_CR39) 2024 V Verma (11367_CR38) 2024; 112 AA Shilnikov (11367_CR21) 2004; 22 Q Lai (11367_CR31) 2023; 53 S Dhall (11367_CR32) 2024; 112 11367_CR43 P Zhou (11367_CR3) 2021; 103 11367_CR42 11367_CR45 11367_CR44 11367_CR47 11367_CR49 Q Lai (11367_CR14) 2022 M Farah (11367_CR6) 2020; 99 Moatsum Alawida (11367_CR48) 2024; 20 11367_CR10 11367_CR12 Shenli Zhu (11367_CR19) 2023; 207 H Wen (11367_CR8) 2022; 10 11367_CR11 11367_CR13 11367_CR16 11367_CR15 X Zhang (11367_CR40) 2023; 111 Y Liu (11367_CR22) 2010; 51 11367_CR50 11367_CR18 11367_CR17 X Wang (11367_CR30) 2023; 111 X Qin (11367_CR33) 2024; 112 11367_CR23 11367_CR25 11367_CR24 X Tong (11367_CR36) 2024; 112 |
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| SubjectTerms | Algorithms Chaos theory Chebyshev approximation Data encryption Design Efficiency Encryption Entropy (Information theory) Flexibility Fractals Internet of Things Mapping Robustness Sequences |
| Title | Chaotic image encryption algorithm based on fractal-chaotic dynamic S-box |
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