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Fast image encryption based on new cascade chaotic system and Rubik’s cube strategy

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Abstract

The strength and effectiveness of a chaotic image cryptosystem are closely related to the complexity of the used chaotic maps. This paper first introduces an enhanced chaotic model called Arc Cotangent and Cotangent Chaotic Model (ACCCM) to generate improved chaotic properties. Dynamical analysis indicates that the enhanced systems exhibit an extensive chaotic range, unpredictable orbit and uniform outputs. In order to improve the strengths and efficiency of encryption, this paper presents a novel image encryption scheme. The scheme consists of a new sequence generator, Rubik’s permutation, and row-wise diffusion. Firstly, the sequence generator is utilized to generate a short keystream for encryption process, where the total keystream only requires 12/m of image size. This module can effectively reduce computational costs and counteract dynamical degradation. Secondly, the permutation phase can randomly break the high spatial correlation by rotating different sections of Rubik’s cube. To further accelerate execution speed while ensuring sufficient security, a row-wise diffusion with random selection is performed to modify pixel values efficiently. Security analysis shows that the scheme has the advantages of high security level and fast running speed. Considering images with a size of 256 × 256, our scheme processes images in real-time at 83 frames per second. This indicates that it is well suited for real-time image encryption tasks.

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Data availability

The datasets generated are available from the corresponding author on reasonable request.

References

  1. Abdelfatah R, Saqr H, Nasr M (2023) An efficient medical image encryption scheme for (WBAN) based on adaptive DNA and modern multi chaotic map. Multimed Tools Appl 82:22213–22227

    Google Scholar 

  2. Alawida M, Samsudin A, Teh J (2019) Enhancing unimodal digital chaotic maps through hybridisation. Nonlinear Dyn 96:601–613

    Google Scholar 

  3. Alawida M, Samsudin A, Teh J et al (2019) A new hybrid digital chaotic system with applications in image encryption. Signal Process 160:45–58

    Google Scholar 

  4. Alawida M, Samsudin A, Teh J et al (2019) Digital cosine chaotic map for cryptographic applications. IEEE Access 7:150609–150622

    Google Scholar 

  5. Alvarez G, Li S (2006) Some basic cryptographic requirements for chaos-based cryptosystems. Int J Bifurc Chaos 16:2129–2151

    MathSciNet  Google Scholar 

  6. Chen L, Yin H, Yuan L (2021) Double color image encryption based on fractional order discrete improved Henon map and Rubik’s cube transform. Signal Process: Image Commun 97:116363

    Google Scholar 

  7. Diaconu A (2016) Circular inter-intra pixels bit-level permutation and chaos-based image encryption. Inf Sci 355–356:314–327

    Google Scholar 

  8. Ding Y, Wu G, Chen D et al (2021) DeepEDN: A deep-learning-based image encryption and decryption network for Internet of medical things. IEEE Internet Things J 8:1504–1518

    Google Scholar 

  9. Elkamchouchi D, Mohamed H, Moussa K (2020) A bijective image encryption system based on hybrid chaotic map diffusion and DNA confusion. Entropy 22:180

    MathSciNet  Google Scholar 

  10. Fang P, Liu H, Wu C et al (2022) A block image encryption algorithm based on a hyperchaotic system and generative adversarial networks. Multimed Tools Appl 81:21811–21857

    Google Scholar 

  11. Fridrich J (1997) Image encryption based on chaotic maps. 1997 IEEE International Conference on Systems, Man, and Cybernetics 2:1105–1110

  12. Guesmi R, Farah M (2021) A new efficient medical image cipher based on hybrid chaotic map and DNA code. Multimed Tools Appl 80:1925–1944

    Google Scholar 

  13. Hu G, Li B (2021) Coupling chaotic system based on unit transform and its applications in image encryption. Signal Process 178:1–17

    Google Scholar 

  14. Hua Z, Jin F, Xu B et al (2018) 2D Logistic-Sine-coupling map for image encryption. Signal Process 149:148–161

    Google Scholar 

  15. Hua Z, Zhou B, Zhou Y (2018) Sine-transform-based chaotic system with FPGA implementation. IEEE Trans Industr Electron 65:2557–2566

    Google Scholar 

  16. Hua Z, Zhou B, Zhou Y (2019) Sine chaotification model for enhancing chaos and its hardware implementation. IEEE Trans Industr Electron 66:1273–1284

    Google Scholar 

  17. Hua Z, Zhou Y, Bao B (2020) Two-dimensional sine chaotification system with hardware implementation. IEEE Trans Industr Inf 16:887–897

    Google Scholar 

  18. Hua Z, Zhou Y, Huang H (2019) Cosine-transform-based chaotic system for image encryption. Inf Sci 480:403–419

    Google Scholar 

  19. Huang X (2012) Image encryption algorithm using chaotic Chebyshev generator. Nonlinear Dyn 67:2411–2417

    MathSciNet  Google Scholar 

  20. Jiang D, Liu L, Zhu L et al (2021) Adaptive embedding: A novel meaningful image encryption scheme based on parallel compressive sensing and slant transform. Signal Process 188:108220

    Google Scholar 

  21. Lan R, He J, Wang S (2018) Integrated chaotic systems for image encryption. Signal Process 147:133–145

    Google Scholar 

  22. Liu B, Xiang H, Liu L (2020) Reducing the dynamical degradation of digital chaotic maps with time-delay linear feedback and parameter perturbation. Math Probl Eng 2020:1–12

    MathSciNet  Google Scholar 

  23. Lorenz E (1963) Deterministic nonperiodic flow. J Atmos Sci 20:130–141

    MathSciNet  Google Scholar 

  24. Lu Q, Zhu C, Deng X (2020) An efficient image encryption scheme based on the LSS chaotic map and single S-Box. IEEE Access 8:25664–25678

    Google Scholar 

  25. Mansouri A, Wang X (2020) A novel one-dimensional sine powered chaotic map and its application in a new image encryption scheme. Inf Sci 520:46–62

    MathSciNet  Google Scholar 

  26. Mansouri A, Wang X (2021) A novel one-dimensional chaotic map generator and its application in a new index representation-based image encryption scheme. Inf Sci 563:91–110

    MathSciNet  Google Scholar 

  27. Naseer Y, Shah T, Attaullah et al (2020) Advance image encryption technique utilizing compression, dynamical system and S-boxes. Math Comput Simul 178:207–217

    MathSciNet  Google Scholar 

  28. National Institute of Standards and Technology (2001) Advanced Encryption Standard (AES). https://csrc.nist.gov/publications/detail/fips/197/final

  29. Pak C, Huang L (2017) A new color image encryption using combination of the 1D chaotic map. Signal Process 138:129–137

    Google Scholar 

  30. Parvaz R, Zarebnia M (2018) A combination chaotic system and application in color image encryption. Opt Laser Technol 101:30–41

    Google Scholar 

  31. Rukhin A, Soto J, Nechvatal J et al (2010) A statistical test suite for random and pseudorandom number generators for cryptographic applications. National Institute of Standards and Technology. http://www.nist.gov/manuscript-publication-search.cfm?pub_id=906762

  32. Sheela S, Suresh K, Tandur D (2018) Image encryption based on modified Henon map using hybrid chaotic shift transform. Multimed Tools Appl 77:25223–25251

    Google Scholar 

  33. Song W, Fu C, Tie M et al (2022) A fast parallel batch image encryption algorithm using intrinsic properties of chaos. Signal Process: Image Commun 102:116628

    Google Scholar 

  34. Vidhya R, Brindha M (2022) A chaos based image encryption algorithm using Rubik’s cube and prime factorization process (CIERPF). J King Saud Univ Comput Inf Sci 34:2000–2016

    Google Scholar 

  35. Wang M, Wang X, Zhang Y et al (2018) A novel chaotic encryption scheme based on image segmentation and multiple diffusion models. Opt Laser Technol 108:558–573

    Google Scholar 

  36. Wang X, Feng L, Li R et al (2019) A fast image encryption algorithm based on non-adjacent dynamically coupled map lattice model. Nonlinear Dyn 95:2797–2824

    Google Scholar 

  37. Wang X, Luan D, Bao X (2014) Cryptanalysis of an image encryption algorithm using Chebyshev generator. Digit Signal Process 25:244–247

    Google Scholar 

  38. Wang X, Zhang J, Gao G (2019) An image encryption algorithm based on ZigZag transform and LL compound chaotic system. Opt Laser Technol 119:105581

    Google Scholar 

  39. Wheeler D, Matthews R (1991) Supercomputer investigations of a chaotic encryption algorithm. Cryptologia 15:140–152

    Google Scholar 

  40. Wu X, Zhu B, Hu Y et al (2017) A novel color image encryption scheme using rectangular transform-enhanced chaotic Tent maps. IEEE Access 5:6429–6436

    Google Scholar 

  41. Wu Y, Noonan J, Agaian S (2011) NPCR and UACI randomness tests for image encryption. Cyber J: J Select Areas Telecommun 1(2):31–38

    Google Scholar 

  42. Xian Y, Wang X, Yan X (2020) Image encryption based on chaotic sub-block scrambling and chaotic digit selection diffusion. Opt Lasers Eng 134:106202

    Google Scholar 

  43. Xiang H, Liu L (2021) A new perturbation-feedback hybrid control method for reducing the dynamic degradation of digital chaotic systems and its application in image encryption. Multimed Tools Appl 80:19237–19261

    Google Scholar 

  44. Xu Q, Sun K, Cao C et al (2019) A fast image encryption algorithm based on compressive sensing and hyperchaotic map. Opt Lasers Eng 121:203–214

    Google Scholar 

  45. Yang C, Taralova I, Assad S et al (2022) Image encryption based on fractional chaotic pseudo-random number generator and DNA encryption method. Nonlinear Dyn 109:2103–2127

    Google Scholar 

  46. Yang S, Tong X, Wang Z et al (2023) S-box generation algorithm based on hyperchaotic system and its application in image encryption. Multimed Tools Appl 82:25559–25583

    Google Scholar 

  47. Yao S, Chen L, Zhong Y (2019) An encryption system for color image based on compressive sensing. Opt Laser Technol 120:105703

    Google Scholar 

  48. Zhang M, Zhang J, Hou A et al (2023) Aerodynamic system instability identification with sample entropy algorithm based on feature extraction. Propulsion Power Res 12:138–152

    Google Scholar 

  49. Zhang Y (2020) Cryptanalyzing an image cryptosystem based on circular inter-intra pixels bit-level permutation. IEEE Access 8:94810–94816

    Google Scholar 

  50. Zhang Y (2020) The fast image encryption algorithm based on lifting scheme and chaos. Inf Sci 520:177–194

    MathSciNet  Google Scholar 

  51. Zhao H, Xie S, Zhang J et al (2020) Efficient image encryption using two-dimensional enhanced hyperchaotic Henon map. J Electron Imaging 29:023007

    Google Scholar 

  52. Zhao H, Xie S, Zhang J et al (2021) A dynamic block image encryption using variable-length secret key and modified Henon map. Optik 230:166307

    Google Scholar 

  53. Zhao J, Zhang T, Jiang J et al (2022) Color image encryption scheme based on alternate quantum walk and controlled Rubik’s Cube. Sci Rep 12:14253

    Google Scholar 

  54. Zheng J, Hu H, Ming H et al (2020) Theoretical design and circuit implementation of novel digital chaotic systems via hybrid control. Chaos Solitons Fractals 138:109863

    MathSciNet  Google Scholar 

  55. Zheng J, Hu H, Xia X (2018) Applications of symbolic dynamics in counteracting the dynamical degradation of digital chaos. Nonlinear Dyn 94:1535–1546

    Google Scholar 

  56. Zhou K, Fan J, Fan H et al (2020) Secure image encryption scheme using double random-phase encoding and compressed sensing. Opt Laser Technol 121:105769

    Google Scholar 

  57. Zhou K, Xu M, Luo J (2019) Cryptanalyzing an image encryption based on a modified Henon map using hybrid chaotic shift transform. Digit Signal Process 93:115–127

    Google Scholar 

  58. Zhou Y, Bao L, Chen C (2014) A new 1D chaotic system for image encryption. Signal Process 97:172–182

    Google Scholar 

  59. Zhou Y, Hua Z, Pun C et al (2015) Cascade chaotic system with applications. IEEE Trans Cybern 45:2001–2012

    Google Scholar 

  60. Zhu C, Sun K (2018) Cryptanalyzing and improving a novel color image encryption algorithm using RT-enhanced chaotic Tent maps. IEEE Access 6:18759–18770

    Google Scholar 

  61. Zhu H, Dai L, Liu Y et al (2021) A three-dimensional bit-level image encryption algorithm with Rubik’s cube method. Math Comput Simul 185:754–770

    MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors did not receive support from any organization for the submitted work.

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Authors and Affiliations

  1. School of Cyberspace Security, Xi’an University of Posts and Telecommunications, Xi’an, China

    Hongxiang Zhao

  2. School of Science, Xi’an University of Posts and Telecommunications, Xi’an, China

    Shucui Xie

  3. College of Mathematics and Information Science, Shaanxi Normal University, Xi’an, China

    Jianzhong Zhang

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  1. Hongxiang Zhao
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Correspondence to Hongxiang Zhao.

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Zhao, H., Xie, S. & Zhang, J. Fast image encryption based on new cascade chaotic system and Rubik’s cube strategy. Multimed Tools Appl 83, 45653–45692 (2024). https://doi.org/10.1007/s11042-023-16936-z

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