Skip to main content
Log in

Image scrambling encryption using chaotic map and genetic algorithm: a hybrid approach for enhanced security

  • Research
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

Image encryption plays a crucial role in safeguarding sensitive visual data from unauthorized access. In this research, we propose a novel hybrid approach for image encryption that combines the strength of chaotic maps and the optimization power of Genetic Algorithm (GA). The proposed method aims to enhance encryption security, complexity, and robustness to various attacks. The encryption process begins with the application of a chaotic map, specifically the Sine fusion chaos, to scramble the positions of image pixels. This chaotic map introduces chaos and non-linearity, rendering the image data indiscernible. In the subsequent step, AES and Genetic Algorithm is introduced to encrypt the image. The GA dynamically evolves the encryption process, aiming to find an optimal cipher image that maximizes encryption security and minimizes the possibility of unauthorized decryption. Experimental results demonstrate that the proposed hybrid approach outperforms traditional image encryption methods in terms of resistance to attacks, robustness, and visual obfuscation. This suggested work demonstrated the algorithm’s resilience to statistical attacks by achieving a maximum entropy of 7.99 and almost zero correlation, despite numerous analyses being conducted on the algorithm. The security analysis reveals the strength of our scheme against various cryptographic attacks. The hybrid encryption technique is suitable for applications requiring heightened image security, such as medical imaging, confidential document transfer, and satellite imagery.

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

Access this article

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

Instant access to the full article PDF.

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

Similar content being viewed by others

Data availibility

Authors confirm that this manuscript has no associated data.

References

  1. Abdullah, A.H., Enayatifar, R., Lee, M.: A hybrid genetic algorithm and chaotic function model for image encryption. AEU-Int. J. Electron. Commun. 66, 806–816 (2012). https://doi.org/10.1016/j.aeue.2012.01.015

    Article  Google Scholar 

  2. Attaullah, Shah, T., Jamal, S.S.: An improved chaotic cryptosystem for image encryption and digital watermarking. Wirel. Pers. Commun. 110, 1429–1442 (2020). https://doi.org/10.1007/s11277-019-06793-1

    Article  Google Scholar 

  3. Belazi, A., Abd El-Latif, A.A., Belghith, S.: A novel image encryption scheme based on substitution-permutation network and chaos. Signal Process. 128, 155–170 (2016). https://doi.org/10.1016/j.sigpro.2016.03.021

    Article  Google Scholar 

  4. Benaissi, S., Chikouche, N., Hamza, R.: A novel image encryption algorithm based on hybrid chaotic maps using a key image. Optik 272, 170316 (2023). https://doi.org/10.1016/j.ijleo.2022.170316

    Article  Google Scholar 

  5. Bhowmik, S., Acharyya, S.: Image encryption approach using improved chaotic system incorporated with differential evolution and genetic algorithm. J. Inf. Secur. Appl. 72, 103391 (2023). https://doi.org/10.1016/j.jisa.2022.103391

    Article  Google Scholar 

  6. Cavusoglu, Ü., Kaçar, S.: A novel parallel image encryption algorithm based on chaos. Cluster Comput. 22, 1211–1223 (2019). https://doi.org/10.1007/s10586-018-02895-w

    Article  Google Scholar 

  7. Chai, X.: An image encryption algorithm based on bit level Brownian motion and new chaotic systems. Multimed. Tools Appl. 76, 1159–1175 (2017). https://doi.org/10.1007/s11042-015-3088-1

    Article  Google Scholar 

  8. Chai, X., Gan, Z., Zhang, M.: A fast chaos-based image encryption scheme with a novel plain image-related swapping block permutation and block diffusion. Multimed. Tools Appl. 76, 15561–15585 (2017). https://doi.org/10.1007/s11042-016-3858-4

    Article  Google Scholar 

  9. Chai, X., Gan, Z., Yuan, K., Chen, Y., Liu, X.: A novel image encryption scheme based on DNA sequence operations and chaotic systems. Neural Comput. Appl. 31, 219–237 (2019). https://doi.org/10.1007/s00521-017-2993-9

    Article  Google Scholar 

  10. Robert, L.D.: Introduction to Chaotic Dynamical Systems. Chapman Hall CRC, Boca Raton (2021)

    Google Scholar 

  11. Enayatifar, R., Abdullah, A.H., Isnin, I.F., Altameem, A., Lee, M.: Image encryption using a synchronous permutation-diffusion technique. Opt. Lasers Eng. 90, 146–154 (2017). https://doi.org/10.1016/j.optlaseng.2016.10.006

    Article  Google Scholar 

  12. Farah, M.B., Guesmi, R., Kachouri, A., Samet, M.: A novel chaos based optical image encryption using fractional Fourier transform and DNA sequence operation. Opt. Laser Technol. 121, 105777 (2020). https://doi.org/10.1016/j.optlastec.2019.105777

    Article  Google Scholar 

  13. Feldman, D.P.: Chaos and Fractals: An Elementary Introduction. Oxford University Press, Oxford (2012)

    Book  Google Scholar 

  14. Fridrich, J.: Symmetric ciphers based on two-dimensional chaotic maps. Int. J. Bifurc. Chaos 8, 1259–1284 (1998). https://doi.org/10.1142/S021812749800098X

    Article  MathSciNet  Google Scholar 

  15. Gayathri, J., Subashini, S.: A survey on security and efficiency issues in chaotic image encryption. Int. J. Inf. Comput. Secur. 8, 347–381 (2016). https://doi.org/10.1504/IJICS.2016.080427

    Article  Google Scholar 

  16. Ghazvini, M., Mirzadi, M., Parvar, N.: A modified method for image encryption based on chaotic map and genetic algorithm. Multimed. Tools Appl. 79, 26927–26950 (2020). https://doi.org/10.1007/s11042-020-09058-3

    Article  Google Scholar 

  17. Hu, T., Liu, Y., Gong, L.H., Ouyang, C.J.: An image encryption scheme combining chaos with cycle operation for DNA sequences. Nonlinear Dyn. 87, 51–66 (2017). https://doi.org/10.1007/s11071-016-3024-6

    Article  Google Scholar 

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

    Article  Google Scholar 

  19. Hussain, S., Asif, M., Shah, T., Mahboob, A., Eldin, S.M.: Redesigning the serpent algorithm by PA-Loop and its image encryption application. IEEE Access 11, 29698–29710 (2023). https://doi.org/10.1109/ACCESS.2023.3261568

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  21. Khalid, I., Shah, T., Eldin, S.M., Shah, D., Asif, M., Saddique, I.: An integrated image encryption scheme based on elliptic curve. IEEE Access 11, 5483–5501 (2022). https://doi.org/10.1109/ACCESS.2022.3230096

    Article  Google Scholar 

  22. Khan, M.: A novel image encryption scheme based on multiple chaotic S-boxes. Nonlinear Dyn. 82, 527–533 (2015). https://doi.org/10.1007/s11071-015-2173-3

    Article  MathSciNet  Google Scholar 

  23. Khan, M., Jamal, S.S., Hazzazi, M.M., Ali, K.M., Hussain, I., Asif, M.: An efficient image encryption scheme based on double affine substitution box and chaotic system. Integration 81, 108–122 (2021). https://doi.org/10.1016/j.vlsi.2021.05.007

    Article  Google Scholar 

  24. Khan, M., Shah, T.: A novel statistical analysis of chaotic S-box in image encryption. 3D Res. 5, 1–8 (2014). https://doi.org/10.1007/s13319-014-0016-5

    Article  Google Scholar 

  25. Lambora, A., Gupta, K., Chopra, K.: Genetic algorithm: a literature review. In: 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon). IEEE, pp. 380–384 (2019). https://doi.org/10.1109/COMITCon.2019.8862255

  26. Li, B., Liao, X., Jiang, Y.: A novel image encryption scheme based on improved random number generator and its implementation. Nonlinear Dyn. 95, 1781–1805 (2019). https://doi.org/10.1007/s11071-018-4659-2

    Article  Google Scholar 

  27. Li, C., Luo, G., Qin, K., Li, C.: An image encryption scheme based on chaotic tent map. Nonlinear Dyn. 87, 127–133 (2017). https://doi.org/10.1007/s11071-016-3030-8

    Article  Google Scholar 

  28. Li, C., Zhang, Y., Xie, E.Y.: When an attacker meets a cipher-image in 2018: a year in review. J. Inf. Secur. Appl. 48, 102361 (2019)

    Google Scholar 

  29. Li, Y., Wang, C., Chen, H.: A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation. Opt. Lasers Eng. 90, 238–246 (2017). https://doi.org/10.1016/j.optlaseng.2016.10.020

    Article  Google Scholar 

  30. Li, Z., Peng, C., Li, L., Zhu, X.: A novel plaintext-related image encryption scheme using hyper-chaotic system. Nonlinear Dyn. 94, 1319–1333 (2018). https://doi.org/10.1007/s11071-018-4426-4

    Article  Google Scholar 

  31. Lin, C.H., Wu, J.X., Chen, P.Y., Lai, H.Y., Li, C.M., Kuo, C.L., Pai, N.S.: Intelligent symmetric cryptography with chaotic map and quantum based key generator for medical images infosecurity. IEEE Access 9, 118624–118639 (2021). https://doi.org/10.1109/ACCESS.2021.3107608

    Article  Google Scholar 

  32. Liu, H., Wang, X.: Color image encryption using spatial bit-level permutation and high-dimension chaotic system. Opt. Commun. 284, 3895–3903 (2011). https://doi.org/10.1016/j.optcom.2011.04.001

    Article  Google Scholar 

  33. Liu, H., Wang, X.: Image encryption using DNA complementary rule and chaotic maps. Appl. Soft Comput. 12, 1457–1466 (2012). https://doi.org/10.1016/j.asoc.2012.01.016

    Article  Google Scholar 

  34. Liu, W., Sun, K., Zhu, C.: A fast image encryption algorithm based on chaotic map. Opt. Lasers Eng. 84, 26–36 (2016). https://doi.org/10.1016/j.optlaseng.2016.03.019

    Article  Google Scholar 

  35. Liu, Y., Wang, J., Fan, J., Gong, L.: Image encryption algorithm based on chaotic system and dynamic S-boxes composed of DNA sequences. Multimed. Tools Appl. 75, 4363–4382 (2016). https://doi.org/10.1007/s11042-015-2479-7

    Article  Google Scholar 

  36. Luo, Y., Ouyang, X., Liu, J., Cao, L.: An image encryption method based on elliptic curve Elgamal encryption and chaotic systems. IEEE Access 7, 38507–38522 (2019). https://doi.org/10.1109/ACCESS.2019.2906052

    Article  Google Scholar 

  37. Mahalingam, H., Veeramalai, T., Menon, A.R., Amirtharajan, R.: Dual-domain image encryption in unsecure medium—a secure communication perspective. Mathematics 11, 1–23 (2023). https://doi.org/10.3390/math11020457

    Article  Google Scholar 

  38. Mahalingam, H., Velupillai Meikandan, P., Thenmozhi, K., Moria, K.M., Lakshmi, C., Chidambaram, N., Amirtharajan, R.: Neural attractor-based adaptive key generator with DNA-coded security and privacy framework for multimedia data in cloud environments. Mathematics 11, 1–23 (2023). https://doi.org/10.3390/math11081769

    Article  Google Scholar 

  39. Mahboob, A., Asif, M., Nadeem, M., Saleem, A., Eldin, S.M., Siddique, I.: A cryptographic scheme for construction of substitution boxes using quantic fractional transformation. IEEE Access 10, 132908–132916 (2022). https://doi.org/10.1109/ACCESS.2022.3230141

    Article  Google Scholar 

  40. Mahboob, A., Asif, M., Siddique, I., Saleem, A., Nadeem, M., Grzelczyk, D., Awrejcewicz, J.: A novel construction of substitution box based on polynomial mapped and finite field with image encryption application. IEEE Access 10, 119244–119258 (2022). https://doi.org/10.1109/ACCESS.2022.3218643

    Article  Google Scholar 

  41. Mahboob, A., Siddique, I., Asif, M., Nadeem, M., Saleem, A.: Construction of highly non linear component of block cipher based on McLaurin series and Mellin transformation with application in image encryption. Multimed. Tools Appl. 83(3), 7159–7177 (2024). https://doi.org/10.1007/s11042-023-15965-y

    Article  Google Scholar 

  42. Mirjalili, S.: Evolutionary Algorithms and Neural Networks. Studies in Computational Intelligence, p. 780. Springer, Berlin (2019)

    Book  Google Scholar 

  43. Mozaffari, S.: Parallel image encryption with bitplane decomposition and genetic algorithm. Multimed. Tools Appl. 77, 25799–25819 (2018). https://doi.org/10.1007/s11042-018-5817-8

    Article  Google Scholar 

  44. Nepomuceno, E.G., Nardo, L.G., Arias-Garcia, J., Butusov, D.N., Tutueva, A.: Image encryption based on the pseudo-orbits from 1D chaotic map. Chaos Interdiscip. J. Nonlinear Sci. (2019). https://doi.org/10.1063/1.5099261

    Article  Google Scholar 

  45. Noshadian, S., Ebrahimzade, A., Kazemitabar, S.J.: Optimizing chaos based image encryption. Multimed. Tools Appl. 77, 25569–25590 (2018). https://doi.org/10.1007/s11042-018-5807-x

    Article  Google Scholar 

  46. Pak, C., Huang, L.: A new color image encryption using combination of the 1D chaotic map. Signal Process. 138, 129–137 (2017). https://doi.org/10.1016/j.sigpro.2017.03.011

    Article  Google Scholar 

  47. Panwar, K., Purwar, R.K., Jain, A.: Cryptanalysis and improvement of a color image encryption scheme based on DNA sequences and multiple 1D chaotic maps. Int. J. Bifurc. Chaos 29(08), 1950103 (2019). https://doi.org/10.1142/S0218127419501037

    Article  MathSciNet  Google Scholar 

  48. Pareek, N.K., Patidar, V., Sud, K.K.: Image encryption using chaotic logistic map. Image Vis. Comput. 24, 926–934 (2006). https://doi.org/10.1016/j.imavis.2006.02.021

    Article  Google Scholar 

  49. Parida, P., Pradhan, C., Gao, X.Z., Roy, D.S., Barik, R.K.: Image encryption and authentication with elliptic curve cryptography and multidimensional chaotic maps. IEEE Access 9, 76191–76204 (2021). https://doi.org/10.1109/ACCESS.2021.3072075

    Article  Google Scholar 

  50. Peitgen, H.O., Jürgens, H., Saupe, D., Feigenbaum, M.J.: Chaos and Fractals: New Frontiers of Science, vol. 106, pp. 560–604. Springer, New York (2004)

    Book  Google Scholar 

  51. Sahari, M.L., Boukemara, I.: A pseudo-random numbers generator based on a novel 3D chaotic map with an application to color image encryption. Nonlinear Dyn. 94, 723–744 (2018). https://doi.org/10.1007/s11071-018-4390-z

    Article  Google Scholar 

  52. Sivanandam, S.N., Sumathi, S., Deepa, S.N.: Introduction to Fuzzy Logic Using MATLAB. Springer, Berlin (2007)

    Book  Google Scholar 

  53. Song, W., Zheng, Y., Fu, C., Shan, P.: A novel batch image encryption algorithm using parallel computing. Inf. Sci. 518, 211–224 (2020). https://doi.org/10.1016/j.ins.2020.01.009

    Article  MathSciNet  Google Scholar 

  54. Tewani, R., Garg, Y., Bagga, J.S., Singh, A., Bhalsodia, R.: Image encryption using permutation-diffusion approach. In: Advances in Data Sciences, Security and Applications: Proceedings of ICDSSA 2019, pp. 363–373. Springer, Singapore (2020)

  55. Wang, X., Feng, L., Li, R., Zhang, F.: A fast image encryption algorithm based on non-adjacent dynamically coupled map lattice model. Nonlinear Dyn. 95, 2797–2824 (2019). https://doi.org/10.1007/s11071-018-4723-y

    Article  Google Scholar 

  56. Wang, X., Wang, Y., Zhu, X., Luo, C.: A novel chaotic algorithm for image encryption utilizing one-time pad based on pixel level and DNA level. Opt. Lasers Eng. 125, 1–12 (2020). https://doi.org/10.1016/j.optlaseng.2019.105851

    Article  Google Scholar 

  57. Wang, X.Y., Li, Z.M.: A color image encryption algorithm based on Hopfield chaotic neural network. Opt. Lasers Eng. 115, 107–118 (2019). https://doi.org/10.1016/j.optlaseng.2018.11.010

    Article  Google Scholar 

  58. Wang, X.Y., Gu, S.X., Zhang, Y.Q.: Novel image encryption algorithm based on cycle shift and chaotic system. Opt. Lasers Eng. 68, 126–134 (2015). https://doi.org/10.1016/j.optlaseng.2014.12.025

    Article  Google Scholar 

  59. Xu, L., Gou, X., Li, Z., Li, J.: A novel chaotic image encryption algorithm using block scrambling and dynamic index based diffusion. Opt. Lasers Eng. 91, 41–52 (2017). https://doi.org/10.1016/j.optlaseng.2016.10.012

    Article  Google Scholar 

  60. Yaghouti Niyat, A., Moattar, M.H.: Color image encryption based on hybrid chaotic system and DNA sequences. Multimed. Tools Appl. 79, 1497–1518 (2020). https://doi.org/10.1007/s11042-019-08247-z

    Article  Google Scholar 

  61. Ye, G.: Image scrambling encryption algorithm of pixel bit based on chaos map. Pattern Recognit. Lett. 31, 347–354 (2010). https://doi.org/10.1016/j.patrec.2009.11.008

    Article  Google Scholar 

  62. Ye, G., Pan, C., Huang, X., Mei, Q.: An efficient pixel-level chaotic image encryption algorithm. Nonlinear Dyn. 94, 745–756 (2018). https://doi.org/10.1007/s11071-018-4391-y

    Article  Google Scholar 

  63. Yosefnezhad Irani, B., Ayubi, P., Amani Jabalkandi, F., Yousefi Valandar, M., Jafari Barani, M.: Digital image scrambling based on a new one-dimensional coupled Sine map. Nonlinear Dyn. 97, 2693–2721 (2019). https://doi.org/10.1007/s11071-019-05157-5

    Article  Google Scholar 

  64. Zhan, K., Wei, D., Shi, J., Yu, J.: Cross-utilizing hyperchaotic and DNA sequences for image encryption. J. Electron. Imaging 26, 013021–013021 (2017). https://doi.org/10.1117/1.JEI.26.1.013021

  65. Zhao, L., Adhikari, A., Xiao, D., Sakurai, K.: On the security analysis of an image scrambling encryption of pixel bit and its improved scheme based on self-correlation encryption. Commun. Nonlinear Sci. Numer. Simul. 17, 3303–3327 (2012). https://doi.org/10.1016/j.cnsns.2011.12.015

  66. Zhu, S., Deng, X., Zhang, W., Zhu, C.: Secure image encryption scheme based on a new robust chaotic map and strong S-box. Math. Comput. Simul. 207, 322–346 (2023). https://doi.org/10.1016/j.matcom.2022.12.025

Download references

Funding

The authors have not received any funding.

Author information

Authors and Affiliations

Authors

Contributions

Both authors contributed to the study conception and design. Material preparation and analysis were performed by S. K. The first draft of the manuscript was written S. K. Supervision, reviewing and editing were done by D. S.

Corresponding author

Correspondence to Deepmala Sharma.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest related to the research presented in this paper.

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 (e.g. a society or other partner) 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, S., Sharma, D. Image scrambling encryption using chaotic map and genetic algorithm: a hybrid approach for enhanced security. Nonlinear Dyn (2024). https://doi.org/10.1007/s11071-024-09670-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11071-024-09670-0

Keywords

Navigation