Skip to main content

Advertisement

Log in

Domain-flexible selective image encryption based on genetic operations and chaotic maps

  • Original article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

Image encryption research has seen massive advances in recent times, but many avenues of improvement still remain nascent. This paper takes head on various research challenges, giving the user fine grained control over their encryption requirements, by proposing a domain-flexible and selective image encryption scheme based on genetic algorithm, chaotic map, square-wave diffusion and orthogonal polynomials transformation. Initially, the proposed cryptosystem separates the image into important and unimportant regions making use of edges in the image with the orthogonal polynomials transformation. Important blocks, termed as Regions of Interest (ROI), are encrypted based on genetic operators and fitness score with chaos and unimportant blocks are encrypted with shuffling operations in the orthogonal polynomial domain. Then, square-wave diffusion is carried on the entire image to obtain the final encrypted image. The novel feature of the proposed encryption scheme is the unique design of the fitness function, wherein the fitness value can be varied between 1 for maximum speed and 10 for maximum security, to suit the user’s requirements and can operate in frequency or spatial or hybrid domain suitable for a vast range of real-time applications. Extensive experiments and analyses have been conducted to demonstrate the efficiency of the proposed work.

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

Similar content being viewed by others

References

  1. Huang, X., Ye, G.: An efficient self-adaptive model for chaotic image encryption algorithm. Commun. Nonlinear Sci. Numer. Simul. 19(12), 4094–4104 (2014). https://doi.org/10.1016/j.cnsns.2014.04.012

    Article  MATH  Google Scholar 

  2. Zhang, Y.Q., Wang, X.Y.: A symmetric image encryption algorithm based on mixed linear–nonlinear coupled map lattice. Inf. Sci. 273, 329–351 (2014). https://doi.org/10.1016/j.ins.2014.02.156

    Article  Google Scholar 

  3. Kadir, A., Hamdullaa, A., Guo, W.-Q.: Color image encryption using skew tent map and hyper chaoticsystem of 6th-order CNN. Optik 125, 1671–1675 (2014)

    Article  Google Scholar 

  4. Khan, M., Masood, F.: A novel chaotic image encryption technique based on multiple discrete dynamical maps. 26203–26222 (2019)

  5. Mandal, M.K., Kar, M., Singh, S.K., Barnwal, V.K.: Symmetric key image encryption using chaotic Rossler system. Secur. Commun. Netw. 7, 2145–2152 (2014)

    Article  Google Scholar 

  6. Praveenkumar, P., Amirtharajan, R., Thenmozhi, K., Rayappan, J.B.B.: Triple chaotic image scrambling on RGB—a random image encryption approach. Secur. Commun. Netw. (2015). https://doi.org/10.1002/sec.1257

    Article  Google Scholar 

  7. Li, S., Zhao, Y., Qu, B., Wang, J.: Image scrambling based on chaotic sequences and Veginere cipher. Multimed. Tools Appl. 66(3), 573–588 (2013). https://doi.org/10.1007/s11042-012-1281-z

    Article  Google Scholar 

  8. Musanna, F., Kumar, S.: A novel fractional order chaos-based image encryption using Fisher Yates algorithm and 3-D cat map (2018)

  9. Muthu, J.S., Murali, P.: Review of chaos detection techniques performed on chaotic maps and systems in image encryption. SN Comput. Sci. 2, 392 (2021). https://doi.org/10.1007/s42979-021-00778-3

    Article  Google Scholar 

  10. Muthu, J.S., Murali, P.: A new chaotic map with large chaotic band for a secured image cryptosystem. Optik 242 (2021). https://doi.org/10.1016/j.ijleo.2021.167300

  11. Liansheng, S., Cong, D., Xiao, Z., Ailing, T., Anand, A.: Double-image encryption based on interference and logistic map under the framework of double random phase encoding. Opt. Lasers Eng. 122, 113–122 (2019). https://doi.org/10.1016/j.optlaseng.2019.06.005

    Article  Google Scholar 

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

    Article  Google Scholar 

  13. Han, C.: An image encryption algorithm based on modified logistic chaotic map. Optik 181, 779–785 (2019). https://doi.org/10.1016/j.ijleo.2018.12.178

    Article  Google Scholar 

  14. Murali, P., Sankaradass, V.: An efficient space filling curve based image encryption. Multimed. Tools Appl. 78(2), 2135–2156 (2019). https://doi.org/10.1007/s11042-018-6234-8

    Article  Google Scholar 

  15. Muthu, J.S., Paul, A.J., Murali, P.: An efficient analyses of the behavior of one dimensional chaotic maps using 0-1 test and three state test. In: 2020 IEEE Recent Advances in Intelligent Computational Systems (RAICS), pp. 125–130. IEEE, Kerala (2020). https://doi.org/10.1109/RAICS51191.2020.9332470

  16. Zeng, L., Liu, R., Zhang, L.Y., Liu, Y., Wong, K.W.: Cryptanalyzing an image encryption algorithm based on scrambling and Veginère cipher. Multimed. Tools Appl. (2015)

  17. Huang, X.: Image encryption algorithm using chaotic Chebyshev Generator. Nonlinear Dyn. 67, 2411–2417 (2012)

    Article  MathSciNet  Google Scholar 

  18. Muthu, J.S., Murali, P.: Optik Comment on “An image encryption algorithm based on modified logistic chaotic map”. Opt. Int. J. Light Electron Opt. 163843 (2019). https://doi.org/10.1016/j.ijleo.2019.163843

  19. Ye, G., Wong, K.: An efficient chaotic image encryption algorithm based on a generalized Arnold map. Nonlinear Dyn. 69(4), 2079–2087 (2012). https://doi.org/10.1007/s11071-012-0409-z

    Article  MathSciNet  Google Scholar 

  20. Shafique, A., Shahid, J.: Novel image encryption cryptosystem based on binary bit planes extraction and multiple chaotic maps. Eur. Phys. J. Plus. 133, 8 (2018). https://doi.org/10.1140/epjp/i2018-12138-3

    Article  Google Scholar 

  21. Luo, Y., Zhou, R., Liu, J., Cao, Y., Ding, X.: A parallel image encryption algorithm based on the piecewise linear chaotic map and hyper-chaotic map

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

    Article  Google Scholar 

  23. Bigdeli, N., Farid, Y., Afshar, K.: A robust hybrid method for image encryption based on Hopfield neural network q. Comput. Electr. Eng. 38(2), 356–369 (2012). https://doi.org/10.1016/j.compeleceng.2011.11.019

    Article  Google Scholar 

  24. Bigdeli, N., Farid, Y., Karim, A.: A novel image encryption/decryption scheme based on chaotic neural networks. Eng. Appl. Artif. Intell. 25, 753–765 (2012)

    Article  Google Scholar 

  25. Babaei, M.: A novel text and image encryption method based on chaos theory and DNA computing. Nat. Comput. 12(1), 101–107 (2012). https://doi.org/10.1007/s11047-012-9334-9

    Article  MathSciNet  MATH  Google Scholar 

  26. Kalpana, J., Murali, P.: An improved color image encryption based on multiple DNA sequence operations with DNA synthetic image and chaos. Optik 126(24), 5703–5709 (2015). https://doi.org/10.1016/j.ijleo.2015.09.091

    Article  Google Scholar 

  27. 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. (2015). https://doi.org/10.1007/s11042-015-2479-7

    Article  Google Scholar 

  28. Rehman, A., Liao, X., Kulsoom, A., ur Rehman, A., Liao, X., Kulsoom, A., Abbas, S.A.: Selective encryption for gray images based on chaos and DNA complementary rules. Multimed. Tools Appl. 74(13), 1–23 (2014). https://doi.org/10.1007/s11042-013-1828-7

  29. Paul, A.J.: Recent advances in selective image encryption and its indispensability due to COVID-19. In: 2020 IEEE Recent Advances in Intelligent Computational Systems (RAICS), pp. 201–206. IEEE, Kerala (2020). https://doi.org/10.1109/RAICS51191.2020.9332513

  30. Khashan, O.A., Zin, A.M., Sundarrajan, A.E.: Performance study of selective encryption in comparison to full encryption for still visual images. J. Zhejiang Univ. Sci. C 15(6), 435–444 (2014)

    Article  Google Scholar 

  31. Ayoup, A.M., Hussein, A.H., Attia, M.A.A.: Efficient selective image encryption. Multimed. Tools Appl. 74(13), 1–16 (2015). https://doi.org/10.1007/s11042-015-2985-7

    Article  Google Scholar 

  32. Bahrami, S., Naderi, M.: Encryption of multimedia content in partial encryption scheme of DCT transform coefficients using a lightweight stream algorithm. Optik 124(18), 3693–3700 (2013). https://doi.org/10.1016/j.ijleo.2012.11.028

    Article  Google Scholar 

  33. Hoang, T.M., Tran, D.: Cryptanalysis and security improvement for selective image encryption. Eur. Phys. J. Spec. Top. 223(8), 1635–1646 (2014)

    Article  Google Scholar 

  34. Krishnamoorthi, R., Malarchelvi, P.D.S.K.: Selective combinational encryption of gray scale images using orthogonal polynomials based transformation. Int. J. Comput. Sci. Netw. Secur. 8(5), 195–204 (2008)

    Google Scholar 

  35. Xiang, T., Wong, K., Liao, X.: Selective image encryption using a spatiotemporal chaotic system. Interdiscip. J. Nonlinear Sci. 17, 2 (2007). https://doi.org/10.1063/1.2728112

    Article  MATH  Google Scholar 

  36. Bhatnagar, G., Wu, Q.M.J.: Selective image encryption based on pixels of interest and singular value decomposition. Digit. Signal Process. 1, 1–16 (2012). https://doi.org/10.1016/j.dsp.2012.02.005

    Article  MathSciNet  Google Scholar 

  37. Krishnamoorthy, R., Murali, P.: A selective image encryption based on square-wave shuffling with orthogonal polynomials transformation suitable for mobile devices. Multimed. Tools Appl. (2015)

  38. Xue, H., Du, J., Li, S., Ma, W.: Region of interest encryption for color images based on a hyperchaotic system with three positive Lyapunov exponets. Opt. Laser Technol. 106, 506–516 (2018). https://doi.org/10.1016/j.optlastec.2018.04.030

    Article  Google Scholar 

  39. Guesmi, R., Ben Farah, M.A., Kachouri, A., Samet, M.: Hash key-based image encryption using crossover operator and chaos. Multimed. Tools Appl. (2015). https://doi.org/10.1007/s11042-015-2501-0

    Article  MATH  Google Scholar 

  40. Enayatifar, R., Abdullah, A.H., Isnin, I.F.: Chaos-based image encryption using a hybrid genetic algorithm and a DNA sequence. Opt. Lasers Eng. 56, 83–93 (2014). https://doi.org/10.1016/j.optlaseng.2013.12.003

    Article  Google Scholar 

  41. Souici, I., Seridi, H., Afdag, H.: Images encryption by the use of evolutionary algorithms. Analog Integr. Circuits Signal Process. 69, 49–58 (2011). https://doi.org/10.1007/s10470-011-9627-4

    Article  Google Scholar 

  42. Gupta, A., Singh, D., Kaur, M.: An efficient image encryption using non‑dominated sorting genetic algorithm—III based 4—D chaotic maps. J. Ambient Intell. Humaniz. Comput. (2019). https://doi.org/10.1007/s12652-019-01493-x

  43. Kumar, J., Nirmala, S.: Encryption of images based on genetic algorithm—a new approach. In: Wyld, D.C., Zizka, J., Nagamalai, D. (eds.) Advances in Computer Science, Engineering & Applications, pp. 783–791. Springer, Berlin (2012)

    Chapter  Google Scholar 

  44. Afrarin, R., Mozaffari, S.: Image encryption using genetic algorithm. In: 8th Iranian Conference on Machine Vision and Image Processing (MVIP) (2013). https://doi.org/10.1109/IranianMVIP.2013.6780026

  45. Pareek, N.K., Patidar, V.: Medical image protection using genetic algorithm operations. Soft Comput. (2014). https://doi.org/10.1007/s00500-014-1539-7

    Article  Google Scholar 

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

  47. Wang, X., Zhang, H.: A novel image encryption algorithm based on genetic recombination and hyper-chaotic systems. Nonlinear Dyn. Online, Cml (2015). https://doi.org/10.1007/s11071-015-2330-8

  48. Ganesan, L., Bhattacharyya, P.: Edge detection in untextured and textured images-a common computational framework. IEEE Trans. Syst. Man Cybern. Soc. Part B 27(5), 823–834 (1997). https://doi.org/10.1109/3477.623235

    Article  Google Scholar 

  49. Krishnamoorthy, R.: Transform coding of monochrome images with a statistical design of experiments approach to separate noise. Pattern Recognit. Lett. 28(7), 771–777 (2007). https://doi.org/10.1016/j.patrec.2006.10.009

    Article  Google Scholar 

  50. Krishnamoorthy, R., Kannan, N.: A new integer image coding technique based on orthogonal polynomials. Image Vis. Comput. 27, 999–1006 (2009)

    Article  Google Scholar 

  51. Kalpana, J., Krishnamoorthy, R.: Color image retrieval technique with local features based on orthogonal polynomials model and SIFT. Multimed. Tools Appl. 75(1), 49–69 (2016)

    Article  Google Scholar 

  52. Krishnamoorthy, R., Kalpana, J.: Fast retrieval of color objects with multidimensional orthogonal polynomials. Multidimens. Syst. Signal Process. 25, 4 (2013). https://doi.org/10.1007/s11045-013-0222-y

    Article  Google Scholar 

  53. Krishnamoorthy, R., Kalpana, J.: Generalized adaptive Bayesian relevance feedback in the orthogonal polynomials domain. Signal Process. 92(12), 3062–3067 (2012)

    Article  Google Scholar 

  54. Krishnamoorthy, R., Sathiyadevi, S.: A multiresolution approach for rotation invariant texture image retrieval with orthogonal polynomials model. J. Vis. Commun. Image Represent. 23(1), 18–30 (2012). https://doi.org/10.1016/j.jvcir.2011.07.011

    Article  Google Scholar 

  55. Wang, L., Ye, Q., Xiao, Y., Zou, Y.: An image encryption scheme based on cross chaotic map. In: 1st International Congress on Image and Signal Processing, pp. 22–26 (2008). https://doi.org/10.1109/CISP.2008.129

  56. Niu, Y., Zhou, Z., Zhang, X.: An image encryption approach based on chaotic maps and genetic operations. Multimed. Tools Appl. 79(35–36), 25613–25633 (2020). https://doi.org/10.1007/s11042-020-09237-2

    Article  Google Scholar 

  57. Premkumar, R., Anand, S.: Secured and compound 3-D chaos image encryption using hybrid mutation and crossover operator. Multimed. Tools Appl. 78(8), 9577–9593 (2019). https://doi.org/10.1007/s11042-018-6534-z

    Article  Google Scholar 

Download references

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. Murali.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest to disclose.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Murali, P., Niranjana, G., Paul, A.J. et al. Domain-flexible selective image encryption based on genetic operations and chaotic maps. Vis Comput 39, 1057–1079 (2023). https://doi.org/10.1007/s00371-021-02384-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-021-02384-z

Keywords

Navigation