Skip to main content
SpringerLink
Log in

A GRU and chaos-based novel image encryption approach for transport images

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

An Intelligent Transport System (ITS) uses smart devices to capture the traffic data in the form of images. However, the adversary can steal and misuse this traffic information. Hence, it becomes essential to have an efficient encryption strategy to save data from various types of attacks. This paper proposes a novel encryption algorithm that uses the Gated Recurrent Unit (GRU) and Sine-Cosine chaotic map to encrypt transport images. The encryption scheme is divided into three phases. In the first phase, two intermediate keys and the seed value required for creating chaotic sequence are generated using unique combinations of 128-bit share key and 128-bit initial vector. In the second phase, permutation is performed using one of the intermediate keys and the chaotic sequence generated by the novel Sine-Cosine chaotic map. The final phase performs the diffusion process using the other intermediate key and GRU approach that uses the chaotic sequence generated by the Sine-Cosine map. The performance of the proposed encryption approach is analyzed using various standard encryption metrics, attacks and decryption parameters. The obtained results and comparative results with existing approaches reveal that the proposed method is suitable for implementing secure and efficient transport image cryptosystems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Adleman LM (1994) Molecular computation of solutions to combinatorial problems. Science (80- ) 266(5187):1021–1024. https://doi.org/10.1126/science.7973651

    Article  Google Scholar 

  2. Bansal M, Kumar M, Sachdeva M, Mittal A (2021) Transfer learning for image classification using VGG19: Caltech-101 image data set. J Ambient Intell Humaniz Comput:1–12

  3. Bansal M, Kumar M, Kumar M (2021) 2D object recognition: a comparative analysis of SIFT, SURF and ORB feature descriptors. Multimed Tools Appl 80(12):18839–18857

    Article  Google Scholar 

  4. Belazi A, Talha M, Kharbech S, Xiang W (2019) Novel medical image encryption scheme based on Chaos and DNA encoding. IEEE Access 7:36667–36681. https://doi.org/10.1109/ACCESS.2019.2906292

    Article  Google Scholar 

  5. Bentoutou Y, Bensikaddour EH, Taleb N, Bounoua N (2020) An improved image encryption algorithm for satellite applications. Adv Sp Res 66(1):176–192. https://doi.org/10.1016/j.asr.2019.09.027

    Article  Google Scholar 

  6. Çavuşoğlu Ü, Kaçar S, Pehlivan I, Zengin A (2017) Secure image encryption algorithm design using a novel chaos based S-Box. Chaos, Solitons Fractals 95:92–101

    Article  MATH  Google Scholar 

  7. Chai X, Chen Y, Broyde L (2017) A novel chaos-based image encryption algorithm using DNA sequence operations. Opt Lasers Eng 88:197–213. https://doi.org/10.1016/j.optlaseng.2016.08.009

    Article  Google Scholar 

  8. Chen J, Zhu Z, Fu C, Yu H (2013) An improved permutation-diffusion type image cipher with a chaotic orbit perturbing mechanism. Opt Express 21(23):27873. https://doi.org/10.1364/oe.21.027873

    Article  Google Scholar 

  9. Chen L, Ma B, Zhao X, Wang S (2017) Differential cryptanalysis of a novel image encryption algorithm based on chaos and line map. Nonlinear Dyn 87(3):1797–1807. https://doi.org/10.1007/s11071-016-3153-y

    Article  MATH  Google Scholar 

  10. Cho K et al. (2014) “Learning phrase representations using RNN encoder-decoder for statistical machine translation,” arXiv Prepr. arXiv1406.1078

  11. Dhall S, Pal SK, Sharma K (2018) A chaos-based probabilistic block cipher for image encryption. J. King Saud Univ. - Comput. Inf. Sci. https://doi.org/10.1016/j.jksuci.2018.09.015

  12. Dou Y, Li M (2021) An image encryption algorithm based on a novel 1D chaotic map and compressive sensing. Multimed Tools Appl 80:1–18

    Article  Google Scholar 

  13. Dua M, Suthar A, Garg A, Garg V (2020) An ILM-cosine transform-based improved approach to image encryption. Complex Intell Syst 7:1–17. https://doi.org/10.1007/s40747-020-00201-z

    Article  Google Scholar 

  14. Fan G-F, Yu M, Dong S-Q, Yeh Y-H, Hong W-C (2021) Forecasting short-term electricity load using hybrid support vector regression with grey catastrophe and random forest modeling. Util Policy 73:101294

    Article  Google Scholar 

  15. Ghazvini M, Mirzadi M, Parvar N (2020) A modified method for image encryption based on chaotic map and genetic algorithm. Multimed Tools Appl 79(37):26927–26950

    Article  Google Scholar 

  16. Guesmi R, Farah MAB (2021) A new efficient medical image cipher based on hybrid chaotic map and DNA code. Multimed Tools Appl 80(2):1925–1944. https://doi.org/10.1007/s11042-020-09672-1

    Article  Google Scholar 

  17. He Y, Zhang Y-Q, He X, Wang X-Y (2021) A new image encryption algorithm based on the OF-LSTMS and chaotic sequences. Sci Rep 11(1):1–22

    Google Scholar 

  18. Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735–1780

    Article  Google Scholar 

  19. Hua Z, Zhou Y (2016) Image encryption using 2D Logistic-adjusted-Sine map. Inf Sci (Ny) 339:237–253. https://doi.org/10.1016/j.ins.2016.01.017

    Article  Google Scholar 

  20. Hua Z, Zhou Y, Pun CM, Chen CLP (2015) 2D Sine Logistic modulation map for image encryption. Inf Sci (Ny) 297:80–94. https://doi.org/10.1016/j.ins.2014.11.018

    Article  Google Scholar 

  21. Hua Z, Zhou Y, Huang H (2019) Cosine-transform-based chaotic system for image encryption. Inf Sci (Ny) 480:403–419. https://doi.org/10.1016/j.ins.2018.12.048

    Article  Google Scholar 

  22. Hua Z, Zhu Z, Yi S, Zhang Z, Huang H (2021) Cross-plane colour image encryption using a two-dimensional logistic tent modular map. Inf Sci (Ny) 546:1063–1083. https://doi.org/10.1016/j.ins.2020.09.032

    Article  MathSciNet  Google Scholar 

  23. Hui Y, Liu H, Fang P (2021) A DNA image encryption based on a new hyperchaotic system. Multimed Tools Appl:1–25

  24. Ismail SM, Said LA, Radwan AG, Madian AH, Abu-Elyazeed MF (2018) Generalized double-humped logistic map-based medical image encryption. J Adv Res 10:85–98

    Article  Google Scholar 

  25. Kaur M, Kumar V (2020) A comprehensive review on image encryption techniques. Arch Comput Methods Eng 27(1):15–43. https://doi.org/10.1007/s11831-018-9298-8

    Article  MathSciNet  Google Scholar 

  26. Kaur M, Singh D, Sun K, Rawat U (2020) Color image encryption using non-dominated sorting genetic algorithm with local chaotic search based 5D chaotic map. Futur Gener Comput Syst 107:333–350

    Article  Google Scholar 

  27. Kumar A, Dua M (2021) Novel pseudo random key & cosine transformed chaotic maps based satellite image encryption. Multimed Tools Appl 80:1–21

    Article  Google Scholar 

  28. Kumar M, Gupta P (2021) A new medical image encryption algorithm based on the 1D logistic map associated with pseudo-random numbers. Multimed Tools Appl 80:1–27

    Article  Google Scholar 

  29. Kumar M, Kumar M (2021) “XGBoost: 2D-object recognition using shape descriptors and extreme gradient boosting classifier,” in Computational Methods and Data Engineering, Springer, pp. 207–222.

  30. Kumar M, Singh N, Kumar R, Goel S, Kumar K (2021) Gait recognition based on vision systems: a systematic survey. J Vis Commun Image Represent 75:103052

    Article  Google Scholar 

  31. Kumar A, Kumar M, Kaur A (2021) Face detection in still images under occlusion and non-uniform illumination. Multimed Tools Appl 80(10):14565–14590

    Article  Google Scholar 

  32. Lalitha R, Srinivasu PN (2017) “An efficient data encryption through image via prime order symmetric key and bit shuffle technique,” in Computer Communication, Networking and Internet Security, Springer, pp. 261–270.

  33. Li Z, Peng C, Tan W, Li L (2021) An effective Chaos-based image encryption scheme using imitating jigsaw method. Complexity 2021:1–18

    Google Scholar 

  34. Lin C-H, Hu G-H, Chan C-Y, Yan J-J (2021) Chaos-Based Synchronized Dynamic Keys and Their Application to Image Encryption with an Improved AES Algorithm. Appl Sci 11(3):1329. https://doi.org/10.3390/app11031329

  35. Liu L, Miao S (2017) An image encryption algorithm based on baker map with varying parameter. Multimed Tools Appl 76(15):16511–16527. https://doi.org/10.1007/s11042-016-3925-x

    Article  Google Scholar 

  36. Liu Y, Zhang LY, Wang J, Zhang Y, Wong KW (2016) Chosen-plaintext attack of an image encryption scheme based on modified permutation–diffusion structure. Nonlinear Dyn 84(4):2241–2250. https://doi.org/10.1007/s11071-016-2642-3

    Article  MATH  Google Scholar 

  37. Liu D, Zhang W, Yu H, Zhu ZL (2018) An image encryption scheme using self-adaptive selective permutation and inter-intra-block feedback diffusion. Signal Process 151:130–143. https://doi.org/10.1016/j.sigpro.2018.05.008

    Article  Google Scholar 

  38. Liu J, Tang S, Lian J, Ma Y, Zhang X (2019) A novel fourth order chaotic system and its algorithm for medical image encryption. Multidim Syst Sign Process 30(4):1637–1657. https://doi.org/10.1007/s11045-018-0622-0

    Article  MATH  Google Scholar 

  39. Ma K, Teng L, Wang X, Meng J (2021) Color image encryption scheme based on the combination of the fisher-yates scrambling algorithm and chaos theory. Multimed Tools Appl 80:1–21

    Article  Google Scholar 

  40. ‘Montauk Student Transport’ n.d. by ThoseGuys119 available at https://www.flickr.com/photos/thoseguys119/45508505011/in/faves-188968346@N07/ under a Creative Commons https://www.flickr.com/photos/thoseguys119/33296487188/. Full terms at https://creativecommons.org/licenses/by/2.0/

  41. Mousavi M, Sadeghiyan B (2021) A new image encryption scheme with Feistel like structure using chaotic S-box and Rubik cube based P-box. Multimed Tools Appl 80(9):13157–13177

    Article  Google Scholar 

  42. ‘one, two, three here we go’ n.d. by Katelyn available at https://www.flickr.com/photos/freakiinkate/3932327519/in/faves-188968346@N07/ under a Creative Commons https://www.flickr.com/photos/thoseguys119/33296487188/. Full terms at https://creativecommons.org/licenses/by/2.0/

  43. Pak C, Kim J, Pang R, Song O, Kim H, Yun I, Kim J (2021) A new color image encryption using 2D improved logistic coupling map. Multimed Tools Appl 80:1–21

    Article  Google Scholar 

  44. Pankaj S, Dua M (2021) A novel ToCC map and two-level scrambling-based medical image encryption technique. Netw Model Anal Heal Informatics Bioinforma 10(1):48. https://doi.org/10.1007/s13721-021-00324-4

    Article  Google Scholar 

  45. Solak E, Çokal C, Yildiz OT, Biyikoǧlu T (2010) Cryptanalysis of fridrich’s chaotic image encryption. Int J Bifurc Chaos 20(5):1405–1413. https://doi.org/10.1142/S0218127410026563

    Article  MathSciNet  MATH  Google Scholar 

  46. Srinivasu PN, Rao S (2015) A multilevel image encryption based on duffing map and modified DNA hybridization for transfer over an unsecured channel. Int J Comput Appl 120(4)

  47. Srinivasu PN, Norwawi N, Amiripalli SS, Deepalakshmi P (2022) Secured compression for 2D medical images through the manifold and fuzzy trapezoidal correlation function. Gazi Univ J Sci 35(4):1372–1391. https://doi.org/10.35378/gujs.884880

  48. Thoms GRW, Muresan R, Al-Dweik A (2019) Chaotic encryption algorithm with key controlled neural networks for intelligent transportation systems. IEEE Access 7:158697–158709

    Article  Google Scholar 

  49. ‘Total Transportation’ n.d. by ThoseGuys119 available at https://www.flickr.com/photos/thoseguys119/45685316451/in/faves-188968346@N07/ under a Creative Commons https://www.flickr.com/photos/thoseguys119/33296487188/. Full terms at https://creativecommons.org/licenses/by/2.0/

  50. ‘Total Transportation’ n.d. by ThoseGuys119 available at https://www.flickr.com/photos/thoseguys119/33296487188/ under a Creative Commons https://www.flickr.com/photos/thoseguys119/33296487188/. Full terms at https://creativecommons.org/licenses/by/2.0/

  51. ‘Vallo Transportation’ n.d. by ThoseGuys119 available at https://www.flickr.com/photos/thoseguys119/47536682812/in/faves-188968346@N07/ under a Creative Commons Attribution 2.0. Full terms at https://creativecommons.org/licenses/by/2.0/.

  52. Walia S, Kumar K, Kumar M, Gao X-Z (2021) Fusion of handcrafted and deep features for forgery detection in digital images. IEEE Access 9:99742–99755. https://doi.org/10.1109/ACCESS.2021.3096240

    Article  Google Scholar 

  53. Wang X, Guan N (2020) Chaotic image encryption algorithm based on block theory and reversible mixed cellular automata. Opt Laser Technol 132:106501

    Article  Google Scholar 

  54. Wang X, Xu D (2014) Image encryption using genetic operators and intertwining logistic map. Nonlinear Dyn 78(4):2975–2984. https://doi.org/10.1007/s11071-014-1639-z

    Article  MathSciNet  Google Scholar 

  55. Wang XY, Zhang YQ, Bao XM (2015) A novel chaotic image encryption scheme using DNA sequence operations. Opt Lasers Eng 73:53–61. https://doi.org/10.1016/j.optlaseng.2015.03.022

    Article  Google Scholar 

  56. Wang J, Zhi X, Chai X, Lu Y (2021) Chaos-based image encryption strategy based on random number embedding and DNA-level self-adaptive permutation and diffusion. Multimed Tools Appl:1–36

  57. Wu Y, Noonan JP, Yang G, Jin H (2012) Image encryption using the two-dimensional logistic chaotic map. J Electron Imaging 21(1):13014

    Article  Google Scholar 

  58. Xiang H, Liu L (2021) A novel image encryption algorithm based on improved key selection and digital chaotic map. Multimed Tools Appl 80:1–28. https://doi.org/10.1007/s11042-021-10807-1

    Article  Google Scholar 

  59. Xu L, Li Z, Li J, Hua W (2016) A novel bit-level image encryption algorithm based on chaotic maps. Opt Lasers Eng 78:17–25. https://doi.org/10.1016/j.optlaseng.2015.09.007

    Article  Google Scholar 

  60. Zareai D, Balafar M, Derakhshi MRF (2021) A new grayscale image encryption algorithm composed of logistic mapping, Arnold cat, and image blocking. Multimed Tools Appl 80:1–28

    Article  Google Scholar 

  61. Zhang X, Ye R (2021) A novel RGB image encryption algorithm based on DNA sequences and chaos. Multimed Tools Appl 80(6):8809–8833

    Article  Google Scholar 

  62. Zhang W, Yu H, Zhao YL, Zhu ZL (2016) Image encryption based on three-dimensional bit matrix permutation. Signal Process 118:36–50. https://doi.org/10.1016/j.sigpro.2015.06.008

    Article  Google Scholar 

  63. Zhang Y-Q, Huang H-F, Wang X-Y, Huang X-H (2021) A secure image encryption scheme based on genetic mutation and MLNCML chaotic system. Multimed Tools Appl 80:1–15

    Google Scholar 

  64. Zhao J, Wang S, Chang Y, Li X (2015) A novel image encryption scheme based on an improper fractional-order chaotic system. Nonlinear Dyn 80(4):1721–1729. https://doi.org/10.1007/s11071-015-1911-x

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  66. Zhu C, Wang G, Sun K (2018) Improved cryptanalysis and enhancements of an image encryption scheme using combined 1D chaotic maps. Entropy 20(11):2399–2413. https://doi.org/10.3390/e20110843

    Article  Google Scholar 

Download references

Funding

This study did not receive any funding from any of the resource.

Author information

Authors and Affiliations

  1. Department of Computer Engineering, National Institute of Technology, Kurukshetra, India

    Atul Kumar & Mohit Dua

Authors
  1. Atul Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohit Dua
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Atul Kumar.

Ethics declarations

Ethics approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Conflict of interest

All the authors and the submitted manuscript do not have any conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, A., Dua, M. A GRU and chaos-based novel image encryption approach for transport images. Multimed Tools Appl 82, 18381–18408 (2023). https://doi.org/10.1007/s11042-022-13902-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-13902-z

Keywords

Search

Navigation