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3D medical model encryption based on five-dimensional hyperchaotic systems with 3D Arnold transform and selectable multiple spiral arrangements

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Abstract

In the era of digitization and informatization, 3D models are used in a variety of fields, notably in medicine, engineering and design, seamlessly integrating into people's daily lives. Particularly within the medical field, 3D models enjoy extensive utilization. Consequently, this paper introduces a novel 3D medical model encryption algorithm, designated as 3D3A-SMA. First, a five-dimensional hyperchaotic system with multiple stability is applied to the encryption process of this algorithm. In this encryption algorithm, the vertex data of the 3D model is divided into integer and fractional parts and different diffusion methods are applied to them, respectively. A 3D Arnold spiral subregion diffusion based on chaotic system (3ASDC) is proposed to diffuse the integer part, and then, a selectable multiple spiral arrangement subregion diffusion (SMASD) is proposed to diffuse the fractional part. The simulation results and performance analysis show that the proposed encryption algorithm can accurately encrypt and decrypt the 3D medical model. The numerical results in the performance analysis are very close to the ideal values, with the information entropy of the ciphertext and each dimension reaching 7.998. In addition, the correlation within the ciphertext is also very close to the ideal value of 0.000, The algorithm also shows strong resistance to common attacks.

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References

  1. Ding P, Wang Z, Li K (2024) Design and analysis of image encryption based on memristor chaotic systems with hidden attractors. Phys Scr 99(7):075252. https://doi.org/10.1088/1402-4896/ad56cf

    Article  Google Scholar 

  2. Islam Y, Li C, Sun K, He S (2024) Enhancing image security through an advanced chaotic system with free control and zigzag scrambling encryption. Multimed Tools Appl 83:67355–67372. https://doi.org/10.1007/s11042-024-18107-0

    Article  Google Scholar 

  3. Lai Q, Liu Y, Yang L (2023) Image encryption using memristive hyperchaos. Appl Intell 53(19):22863–22881. https://doi.org/10.1007/s10489-023-04727-w

    Article  Google Scholar 

  4. Singh HK, Singh AK (2023) Digital image watermarking using deep learning. Multimed Tools Appl 83:2979–2994. https://doi.org/10.1007/s11042-023-15750-x

    Article  Google Scholar 

  5. Wang X, Ma RT, Xu X, Niu P, Yang H (2023) Non-linear statistical image watermark detector. Appl Intell 53(23):29242–29266. https://doi.org/10.1007/s10489-023-05061-x

    Article  Google Scholar 

  6. Wang B, Shen L, Zhang J, Xu Z, Wang N (2023) A text image watermarking algorithm based on image enhancement. Cmc-Comput Mater Con 77(1):1183–1207. https://doi.org/10.32604/cmc.2023.040307

    Article  Google Scholar 

  7. Wang T, Cheng H, Liu X, Xu Y, Chen F et al (2024) Lossless image steganography: regard steganography as super-resolution. Inform Process Manag. https://doi.org/10.1016/j.ipm.2024.103719

    Article  Google Scholar 

  8. Qin T, Feng B, Chen B, Peng Z, Xia Z et al (2024) Moiré pattern generation-based image steganography. J Inf Secur Appl. https://doi.org/10.1016/j.jisa.2024.103753

    Article  Google Scholar 

  9. Zhang L, Lu Y, Li T, Lu G (2023) Joint adjustment image steganography networks. Signal Process-Image. https://doi.org/10.1016/j.image.2023.117022

    Article  Google Scholar 

  10. Wang X, Xu M, Li Y (2019) Fast encryption scheme for 3D models based on chaos system. Multimed Tools Appl 78(23):33865–33884. https://doi.org/10.1007/s11042-019-08171-2

    Article  Google Scholar 

  11. Liang Y, He F, Li H (2019) An asymmetric and optimized encryption method to protect the confidentiality of 3D mesh model. Adv Eng Inform. https://doi.org/10.1016/j.aei.2019.100963

    Article  Google Scholar 

  12. Gao S, Wu R, Wang X et al (2023) A 3D model encryption scheme based on a cascaded chaotic system. Signal Process 202:108745. https://doi.org/10.1016/j.sigpro.2022.108745

    Article  Google Scholar 

  13. Lu Y, Gong M, Gan Z et al (2023) Exploiting one-dimensional improved Chebyshev chaotic system and partitioned diffusion based on the divide-and-conquer principle for 3D medical model encryption. Chaos Soliton Fract 171:113449. https://doi.org/10.1016/j.chaos.2023.113449

    Article  MathSciNet  Google Scholar 

  14. Gao X, Miao M, Chen X (2022) Multi-image encryption algorithm for 2D and 3D images based on chaotic system. Front Phys-Lausanne. https://doi.org/10.3389/fphy.2022.901800

    Article  Google Scholar 

  15. Elkhalil N, Weddy YC, Ejbali R (2023) Image encryption using the new two-dimensional Beta chaotic map. Multimed Tools Appl 82(20):31575–31589. https://doi.org/10.1007/s11042-023-15105-6

    Article  Google Scholar 

  16. Liu S, Li C, Li Y (2022) A novel image encryption algorithm based on exponent-cosine chaotic mapping. J Electron Inf Techn 44(5):1754–1762. https://doi.org/10.11999/JEIT210270

    Article  Google Scholar 

  17. Liu L, Wang J (2023) A cluster of 1D quadratic chaotic map and its applications in image encryption. Math Comput Simulat 204:89–114. https://doi.org/10.11999/JEIT210270

    Article  MathSciNet  Google Scholar 

  18. Shraida GK, Younis HA, Al-Amiedy TA et al (2023) An efficient color-image encryption method using DNA sequence and chaos cipher. Cmc-Comput Mater Con 75(2):2641–2654. https://doi.org/10.32604/cmc.2023.035793

    Article  Google Scholar 

  19. Xue X, Jin H, Zhou D, Zhou C (2021) Medical image protection algorithm based on deoxyribonucleic acid chain of dynamic length. Front Genet 12:654663. https://doi.org/10.3389/fgene.2021.654663

    Article  Google Scholar 

  20. Wu Y, Zhang L, Berretti S, Wang S (2023) Medical image encryption by content-aware DNA computing for secure healthcare. IEEE T Ind Inform 19(2):2089–2098. https://doi.org/10.1109/TII.2022.3194590

    Article  Google Scholar 

  21. Lee H, Lee J, Kim H, Mu D (2022) Dataset and method for deep learning-based reconstruction of 3D CAD models containing machining features for mechanical parts. J Comput Des Eng 9(1):114–127. https://doi.org/10.1093/jcde/qwab072

    Article  Google Scholar 

  22. Xiao J, Li Y, Tian Y et al (2022) Visual recognition of cardiac pathology based on 3D parametric model reconstruction. Front Inform Technol Electron Eng 23(9):1324–1337. https://doi.org/10.1631/FITEE.2200102

    Article  Google Scholar 

  23. Mizher MA, Sulaiman R, Abdalla AM, Mizher MA (2019) An improved simple flexible cryptosystem for 3D objects with texture maps and 2D images. J Inf Secur Appl 47:390–409. https://doi.org/10.1016/j.jisa.2019.06.005

    Article  Google Scholar 

  24. Xu J, Zhao C, Mou J (2020) A 3D image encryption algorithm based on the chaotic system and the image segmentation. IEEE Access 8:145995–146005. https://doi.org/10.1109/ACCESS.2020.3005925

    Article  Google Scholar 

  25. Hu Y, Wang X, Zhang L (2022) 1D sine-map-coupling-logistic-map for 3D model encryption. Front Phys-Lausanne 10:1006324. https://doi.org/10.3389/fphy.2022.1006324

    Article  Google Scholar 

  26. van Rensburg BJ, Puech W, Pedeboy J (2023) A format compliant encryption method for 3D objects allowing hierarchical decryption. IEEE T Multimed 25:7196–7207. https://doi.org/10.1109/TMM.2022.3219616

    Article  Google Scholar 

  27. Li S, Zhao R, Guan Q, Chen J, Zhang Y (2024) A 3D model encryption method supporting adaptive visual effects after decryption. Adv Eng Inform 59:102319. https://doi.org/10.1016/j.aei.2023.102319

    Article  Google Scholar 

  28. Joshi M, Bhatt V, Ranjan A (2023) A single parametrically controlled megastable multiscroll attractor with an unstable node. The European Phys J B. https://doi.org/10.1140/epjb/s10051-023-00535-w

    Article  Google Scholar 

  29. Bhatt V, Ranjan A, Joshi M (2024) CCCCTA-based chua’s circuit for chaotic oscillation. Circ Syst Signal Pr 43(4):2051–2072. https://doi.org/10.1007/s00034-023-02579-w

    Article  Google Scholar 

  30. Joshi M, Ranjan A (2021) Dual feedback IRC ring for chaotic waveform generation. Iet Circ Device Syst 15(7):595–601. https://doi.org/10.1049/cds2.12054

    Article  Google Scholar 

  31. Zhong H, Li G, Xu X (2022) A generic voltage-controlled discrete memristor model and its application in chaotic map. Chaos Soliton Fract 161:112389. https://doi.org/10.1016/j.chaos.2022.112389

    Article  MathSciNet  Google Scholar 

  32. Yu F, Zhang W, Xiao X et al (2023) Dynamic analysis and FPGA implementation of a new, simple 5D memristive hyperchaotic sprott-C system. Mathematics-Basel 11(3):701. https://doi.org/10.3390/math11030701

    Article  Google Scholar 

  33. Wu C (2014) An improved discrete Arnold transform and its application in image scrambling and encryption. Acta Phys Sin-Ch Ed. https://doi.org/10.7498/aps.63.090504

    Article  Google Scholar 

  34. Chen H, Du X, Liu Z (2016) Optical hyperspectral data encryption in spectrum domain by using 3D Arnold and gyrator transforms. Spectrosc Lett 49(2):103–107. https://doi.org/10.1080/00387010.2015.1089447

    Article  Google Scholar 

  35. Xu J, Zhao B (2023) Designing an image encryption algorithm based on hyperchaotic system and DCT. Int J Bifurcat Chaos 33(2):2350021. https://doi.org/10.1142/S0218127423500219

    Article  MathSciNet  Google Scholar 

  36. Jin X, Zhaoxing W, Song C, Zhang C, Li X (2016) 3d point cloud encryption through chaotic mapping. In: Chen E, Gong Y, Tie Y (eds) Advances in Multimedia Information Processing - PCM 2016. Springer International Publishing, Cham, pp 119–129. https://doi.org/10.1007/978-3-319-48890-5_12

    Chapter  Google Scholar 

  37. Sun J (2021) A 3D image encryption algorithm based on chaos and random cross diffusion. Mod Phys Lett B 35(30):2150465. https://doi.org/10.1142/S0217984921504650

    Article  MathSciNet  Google Scholar 

  38. Jin X, Zhu S, Xiao C, Sun H, Li X et al (2017) 3D textured model encryption via 3D Lu chaotic mapping. Sci China Inf Sci 60(12):122107. https://doi.org/10.1007/s11432-017-9266-1

    Article  Google Scholar 

  39. Chu R, Zhang S, Gao X (2022) A novel 3D image encryption based on the chaotic system and RNA crossover and mutation. Front Phys. https://doi.org/10.3389/fphy.2022.844966

    Article  Google Scholar 

  40. Xu J, Mou J, Xiong L, Li P, Hao J (2021) A flexible image encryption algorithm based on 3D CTBCS and DNA computing. Multimed Tools Appl 80(17):25711–25740. https://doi.org/10.1007/s11042-021-10764-9

    Article  Google Scholar 

  41. Raghunandan KR, Dodmane R, Bhavya K, Sahu AK (2023) Chaotic-map based encryption for 3D point and 3D mesh fog data in edge computing. IEEE Access 11:3545–3554. https://doi.org/10.1109/ACCESS.2022.3232461

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Natural Science Foundation of China (No. 61801173).

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Authors and Affiliations

  1. Electronic Engineering College, Heilongjiang University, Harbin, 150080, China

    Jianing Li, Wenjing Zhang & Bing Zhao

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  1. Jianing Li
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Contributions

J.L. was involved in writing-original draft. W.Z. was responsible for methodology and software. B.Z. was responsible for writing-reviewing and editing.

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Correspondence to Bing Zhao.

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Li, J., Zhang, W. & Zhao, B. 3D medical model encryption based on five-dimensional hyperchaotic systems with 3D Arnold transform and selectable multiple spiral arrangements. J Supercomput 81, 39 (2025). https://doi.org/10.1007/s11227-024-06483-1

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