Skip to main content
Springer Nature Link
Log in

Metaheuristic-supported image encryption framework based on binary search tree and DNA encoding

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

Abstract

Rapid evolution in digital communication increases the risk of unauthorized access to sensitive data. Digital images are one of the most popular types and are frequently used to share various information including many sensitive data. Hence, security of the digital images is one of the major concerns for reliable data communication. This work addresses this issue and proposes a novel image encryption technique in which the concept of the binary search tree is introduced. The structure of the binary search tree is optimized with the help of the electromagnetism-like optimization approach that optimizes the image entropy. The proposed approach also incorporates the concept of DNA (Deoxyribonucleic acid) encoding and based on this concept bitplane decomposition is used to get DNA bit planes. A scrambling approach is also proposed to add an additional layer of security. This approach is a symmetric image encryption scheme and is completely lossless. The performance of this approach is tested in terms of both qualitative and quantitative manner. Experimental results and comparative outcomes with the state-of-the-art approaches are encouraging and prove the efficiency of the proposed approach.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Algorithm 1
Algorithm 2
Algorithm 3
Algorithm 4
Fig. 2
Fig. 3
Fig. 4
Algorithm 5
Fig. 5
Algorithm 6
Algorithm 7
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

References

  1. Abdulla AA (2015) Exploiting similarities between secret and cover images for improved embedding efficiency and security in digital steganography (Doctoral dissertation, University of Buckingham)

  2. Amari SI (1993) Backpropagation and stochastic gradient descent method. Neurocomputing 5(4–5):185–196

  3. Bao L,  Zhou Y (2015) Image encryption: Generating visually meaningful encrypted images. Inf Sci 324:197–207

  4. Birbil ŞI, Fang SC (2003) An electromagnetism-like mechanism for global optimization. J Glob Optim 25:263–282. https://doi.org/10.1023/A:1022452626305

    Article  MathSciNet  Google Scholar 

  5. Chakraborty S, Mali K (2020) SuFMoFPA: a superpixel and meta-heuristic based fuzzy image segmentation approach to explicate COVID-19 radiological images. Expert Syst Appl 114142. https://doi.org/10.1016/j.eswa.2020.114142

  6. Chakraborty S, Mali K (2020) Fuzzy electromagnetism optimization (FEMO) and its application in biomedical image segmentation. Appl Soft Comput J 97. https://doi.org/10.1016/j.asoc.2020.106800

  7. Chakraborty S, Seal A, Roy M, Mali K (2016) A novel lossless image encryption method using DNA substitution and chaotic logistic map. Int J Secur its Appl 10:. https://doi.org/10.14257/ijsia.2016.10.2.19

  8. Chakraborty S, Chatterjee S, Dey N, Ashour AS, Ashour AS, Shi F, Mali K (2017) Modified cuckoo search algorithm in microscopic image segmentation of hippocampus. Microscopy Research and Technique 80(10):1051–1072

  9. Computer security division N FIPS 46-3, data encryption standard (DES) (withdrawn May 19, 2005)

  10. Cui G, Qin L, Wang Y, Zhang X (2008) An encryption scheme using DNA technology. In: 2008 3rd international conference on bio-inspired computing: theories and applications. IEEE, pp 37–42

  11. Daemen J, Rijmen V (1998) The block cipher Rijndael. In International Conference on Smart Card Research and Advanced Applications. Berlin, Springer pp. 277–284

  12. Enayatifar R, Abdullah AH, Lee M (2013) A weighted discrete imperialist competitive algorithm (WDICA) combined with chaotic map for image encryption. Opt Lasers Eng 51:1066–1077. https://doi.org/10.1016/j.optlaseng.2013.03.010

    Article  Google Scholar 

  13. Gálvez J, Cuevas E, Avalos O, Oliva D, Hinojosa S (2018) Electromagnetism-like mechanism with collective animal behavior for multimodal optimization. Appl Intell 48:2580–2612

  14. Gehani A, LaBean T, Reif J (2004) DNA-based cryptography. Aspects of molecular computing: essays dedicated to tom head, on the occasion of his 70th birthday, 167–188

  15. Gehani A, La Bean T, Reif JH DNA-based cryptography. DIMACS series in discrete mathematics. Theor Comput Sci 54:233–249

  16. Grangetto M, Magli E, Olmo G (2006) Multimedia selective encryption by means of randomized arithmetic coding. IEEE Trans Multimed 8:905–917. https://doi.org/10.1109/TMM.2006.879919

    Article  Google Scholar 

  17. Hu J, Han F (2009) A pixel-based scrambling scheme for digital medical images protection. J Netw Comput Appl 32:788–794. https://doi.org/10.1016/J.JNCA.2009.02.009

    Article  Google Scholar 

  18. Hua Z, Zhou Y, Pun C-M, 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 

  19. 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 

  20. Kamali SH, Hedayati M, Shakerian R, Rahmani M (2010) A new modified version of advanced encryption standard based algorithm for image encryption. In: ICEIE 2010 - 2010 International Conference on Electronics and Information Engineering, Proceedings

  21. Khan HN, Chaudhuri A, Das A, Chaudhuri A (2019) An ultra robust session key based image cryptography. Microsyst Technol 1–9. https://doi.org/10.1007/s00542-019-04518-9

  22. Leong MP, Cheung OYH, Tsoi KH, Leong PHW A bit-serial implementation of the international data encryption algorithm IDEA. In: Proceedings 2000 IEEE Symposium on Field-Programmable Custom Computing Machines (Cat. No.PR00871). IEEE Comput Soc, pp 122–131

  23. Li L, Xie Y, Liu B et al (2019) Optical image encryption and transmission with semiconductor lasers. Opt Laser Technol 119:105616. https://doi.org/10.1016/j.optlastec.2019.105616

    Article  Google Scholar 

  24. Lindholm FA, Fossum JG, Burgess EL (1979) Application of the superposition principle to solar-cell analysis. IEEE Trans Electron Devices 26:165–171. https://doi.org/10.1109/T-ED.1979.19400

    Article  ADS  Google Scholar 

  25. Mali K, Chakraborty S, Seal A, Roy M (2015) An efficient image cryptographic algorithm based on frequency domain using Haar wavelet transform. Int J Secur its Appl 9:279–288. https://doi.org/10.14257/ijsia.2015.9.12.26

    Article  Google Scholar 

  26. Mali K, Chakraborty S, Roy M (2015) A study on statistical analysis and security evaluation parameters in image encryption. IJSRD-International J Sci Res Dev 3:2321–0613

    Google Scholar 

  27. Pareek N, Patidar V, Sud K (2003) Discrete chaotic cryptography using external key. Phys Lett A 309:75–82. https://doi.org/10.1016/S0375-9601(03)00122-1

    Article  ADS  MathSciNet  CAS  Google Scholar 

  28. Patidar V, Sud K, Informatica NP, (2009) Undefined A pseudo random bit generator based on chaotic logistic map and its statistical testing. informatica.si

  29. Roy M, Mali K, Chatterjee S, et al (2019) A study on the applications of the biomedical image encryption methods for secured computer aided diagnostics. In: proceedings - 2019 Amity International conference on artificial intelligence, AICAI 2019

  30. Roy M, Chakraborty S, Mali K, et al (2019) A dual layer image encryption using polymerase chain reaction amplification and dna encryption. In 2019 international conference on optoelectronics and applied optics (Optronix). IEEE  (pp. 1–4)

  31. Roy M, Chakraborty S, Mali K (2020) A robust image encryption method using chaotic skew-tent map. In: Chakraborty S, Mali K (eds) Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities

  32. Roy M, Chakraborty S, Mali K et al (2020) Biomedical image security using matrix manipulation and DNA encryption. In: Advances in intelligent systems and computing. Springer, pp 49–60

    Google Scholar 

  33. Roy M, Chakraborty S, Mali K,  et al (2020) Data security techniques based on DNA encryption. In Proceedings of International Ethical Hacking Conference 2019: eHaCON 2019, Kolkata, India. Springer, Singapore  (pp. 239–249)

  34. Roy M, Chakraborty S, Mali K (2021) A chaotic framework and its application in image encryption. Multimedia Tools Appl 80:24069–24110

  35. Roy M, Chakraborty S, Mali K (2021) The MSK: a simple and robust image encryption method. Multimed Tools Appl 80:21261–21291

  36. Roy M, Chakraborty S, Mali K, et al (2021) A robust image encryption framework based on DNA computing and chaotic environment. Microsyst Technol 1–11. https://doi.org/10.1007/s00542-020-05120-0

  37. Roy M, Chakraborty S, Mali K et al (2021) An image security method based on low dimensional chaotic environment and DNA encoding. Springer, Singapore, pp 267–277

    Google Scholar 

  38. Roy M, Chakraborty S, Mali K, Roy D (2021) Utilization of Hyperchaotic environment and DNA sequences for digital image security. Advances in smart communication technology and information processing: OPTRONIX 2020. Springer, Singapore

  39. Seal A, Chakraborty S, Mali K (2017) A new and resilient image encryption technique based on pixel manipulation, value transformation and visual transformation utilizing single–level haar wavelet transform

  40. Shujun L, Xuanqin M, Yuanlong C (2001) Pseudo-random bit generator based on couple chaotic systems and its applications in stream-cipher cryptography. Springer, Berlin, Heidelberg, pp 316–329

    Google Scholar 

  41. Sun F, Lu Z, Liu S (2010) A new cryptosystem based on spatial chaotic system. Opt Commun 283:2066–2073. https://doi.org/10.1016/j.optcom.2010.01.028

    Article  ADS  CAS  Google Scholar 

  42. Suri S, Vijay R (2019) A bi-objective genetic algorithm optimization of Chaos-DNA based hybrid approach. J Intell Syst 28:333–346. https://doi.org/10.1515/jisys-2017-0069

    Article  Google Scholar 

  43. Tsamardinos I, Brown LE, Aliferis CF (2006) The max-min hill-climbing Bayesian network structure learning algorithm. Mach Learn 65:31–78. https://doi.org/10.1007/s10994-006-6889-7

    Article  Google Scholar 

  44. Wadi SM, Zainal N (2014) High definition image encryption algorithm based on AES modification. Wirel Pers Commun 79:811–829. https://doi.org/10.1007/s11277-014-1888-7

    Article  Google Scholar 

  45. Wang X, Zhang Q (2009) DNA computing-based cryptography. In: 2009 fourth international on conference on bio-inspired computing. IEEE, pp 1–3

  46. Wang X, Liu L, Zhang Y (2015) A novel chaotic block image encryption algorithm based on dynamic random growth technique. Opt Lasers Eng 66:10–18. https://doi.org/10.1016/J.OPTLASENG.2014.08.005

    Article  Google Scholar 

  47. Wu Y, Zhou Y, Noonan JP, Agaian S (2014) Design of image cipher using latin squares. Inf Sci (Ny) 264:317–339. https://doi.org/10.1016/J.INS.2013.11.027

    Article  MathSciNet  Google Scholar 

  48. Wu X, Wang D, Kurths J, Kan H (2016) A novel lossless color image encryption scheme using 2D DWT and 6D hyperchaotic system. Inf Sci (Ny) 349–350:137–153. https://doi.org/10.1016/J.INS.2016.02.041

    Article  Google Scholar 

  49. Xu M, Tian Z (2019) A novel image cipher based on 3D bit matrix and latin cubes. Inf Sci (Ny) 478:1–14. https://doi.org/10.1016/J.INS.2018.11.010

    Article  ADS  Google Scholar 

  50. Ye R (2011) A novel chaos-based image encryption scheme with an efficient permutation-diffusion mechanism. Opt Commun 284:5290–5298. https://doi.org/10.1016/j.optcom.2011.07.070

    Article  ADS  CAS  Google Scholar 

  51. Zahmoul R, Ejbali R, Zaied M (2017) Image encryption based on new Beta chaotic maps. Opt Lasers Eng 96:39–49. https://doi.org/10.1016/J.OPTLASENG.2017.04.009

    Article  Google Scholar 

  52. Zhang Y (2018) The unified image encryption algorithm based on chaos and cubic S-box. Inf Sci (Ny) 450:361–377. https://doi.org/10.1016/J.INS.2018.03.055

    Article  ADS  MathSciNet  Google Scholar 

  53. Zhang W, Yu H, Zhao Y, Zhu Z (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 

  54. Zhou Y, Panetta K, Agaian S, Chen CLP (2013) (n, k, p)-gray code for image systems. IEEE Trans Cybern 43:515–529. https://doi.org/10.1109/TSMCB.2012.2210706

    Article  PubMed  Google Scholar 

  55. Zhou Y, Cao W, Philip Chen CL (2014) Image encryption using binary bitplane. Signal Process 100:197–207. https://doi.org/10.1016/J.SIGPRO.2014.01.020

    Article  Google Scholar 

  56. Zhu Z, Zhang W, Wong K, Yu H (2011) A chaos-based symmetric image encryption scheme using a bit-level permutation. Inf Sci (Ny) 181:1171–1186. https://doi.org/10.1016/J.INS.2010.11.009

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, University of Kalyani, Kalyani, India

    Mousomi Roy, Shouvik Chakraborty & Kalyani Mali

Authors
  1. Mousomi Roy
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Shouvik Chakraborty
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Kalyani Mali
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Shouvik Chakraborty.

Ethics declarations

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported 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

Roy, M., Chakraborty, S. & Mali, K. Metaheuristic-supported image encryption framework based on binary search tree and DNA encoding. Multimed Tools Appl 83, 25321–25349 (2024). https://doi.org/10.1007/s11042-023-16471-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-023-16471-x

Keywords