Skip to main content

Advertisement

Log in

Remote sensing image encryption algorithm based on DNA convolution

  • Research
  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Remote sensing images carry geospatial information with significant military and economic implications. While the open network environment facilitates efficient image transmission, it also raises security concerns. To address this, we propose a remote sensing image encryption algorithm based on a novel Exponent-Sine-Logistic (ESL) map and DNA convolution. The algorithm employs a scrambling-diffusion framework within the DNA domain. In the scrambling phase, the DNA codes of multiple images are scrambled using a chaotic sequence generated by the ESL map. In the diffusion phase, the scrambled DNA codes are further modified using DNA convolution, integrating multiple DNA operations to enhance security. Additionally, the algorithm improves efficiency through fast dynamic DNA encoding and decoding methods. Experimental results show that the algorithm achieves an information entropy of 7.9998 and encrypts four 256 × 256 images in just 0.7455 s. The algorithm demonstrates superior security and efficiency, effectively resisting common attacks, making it highly applicable in military and surveying fields.

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

Access this article

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Algorithm 1
Algorithm 2
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Yu Z, Yang Z (2021) Method of remote sensing image detail encryption based on symmetry algorithm. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02818-x

    Article  MATH  Google Scholar 

  2. Zhang D, Ren L, Shafiq M, Gu Z (2022) A lightweight privacy-preserving system for the security of remote sensing images on IoT. Remote Sens-Basel 14(24):6371. https://doi.org/10.3390/rs14246371

    Article  MATH  Google Scholar 

  3. Nan S, Feng X, Wu Y, Zhang H (2022) Remote sensing image compression and encryption based on block compressive sensing and 2D-LCCCM. Nonlinear Dynam 108(3):2705–2729. https://doi.org/10.1007/s11071-022-07335-4

    Article  MATH  Google Scholar 

  4. Hagras T, Salama D, Youness H (2022) Anti-attacks encryption algorithm based on DNA computing and data encryption standard. Alex Eng J 61(12):11651–11662. https://doi.org/10.1016/j.aej.2022.05.033

    Article  MATH  Google Scholar 

  5. Sahin ME (2023) Memristive chaotic system-based hybrid image encryption application with AES and RSA algorithms. Phys Scr 98(7):75216. https://doi.org/10.1088/1402-4896/acdba0

    Article  MATH  Google Scholar 

  6. Zhou J, Zhou N, Gong L (2020) Fast color image encryption scheme based on 3D orthogonal Latin squares and matching matrix. Opt Laser Technol 131:106437. https://doi.org/10.1016/j.optlastec.2020.106437

    Article  MATH  Google Scholar 

  7. Liu Z, Li J, Di X, Man Z, Sheng Y (2021) A novel multiband remote-sensing image encryption algorithm based on dual-channel key transmission model. Secur Commun Netw 2021:9698371. https://doi.org/10.1155/2021/9698371

    Article  MATH  Google Scholar 

  8. Xin J, Hu H, Zheng J (2023) 3D variable-structure chaotic system and its application in color image encryption with new Rubik’s Cube-like permutation. Nonlinear Dynam 111(8):7859–7882. https://doi.org/10.1007/s11071-023-08230-2

    Article  MATH  Google Scholar 

  9. Belmar-Monterrubio R, Quiroz-Ibarra JE, Cervantes-Sodi F (2023) A versatile mathematical function for generating stable and chaotic systems: a data encryption application. Chaos Solitons Fractals 167:113047. https://doi.org/10.1016/j.chaos.2022.113047

    Article  MathSciNet  Google Scholar 

  10. Wang C, Song L (2023) An image encryption scheme based on chaotic system and compressed sensing for multiple application scenarios. Inf Sci 642:119166. https://doi.org/10.1016/j.ins.2023.119166

    Article  Google Scholar 

  11. Yan F, Shen Y, Zou T, Wu Z, Su Y (2023) A novel spectrogram visual security encryption algorithm based on block compressed sensing and five-dimensional chaotic system. Nonlinear Dynam 111(10):9607–9628. https://doi.org/10.1007/s11071-023-08317-w

    Article  Google Scholar 

  12. Lu Y, Gong M, Cao L, Gan Z, Chai X, Li A (2023) Exploiting 3D fractal cube and chaos for effective multi-image compression and encryption. J King Saud Univ Comput Inf Sci 35(3):37–58. https://doi.org/10.1016/j.jksuci.2023.02.004

    Article  MATH  Google Scholar 

  13. Rezaei B, Ghanbari H, Enayatifar R (2023) An image encryption approach using tuned Henon chaotic map and evolutionary algorithm. Nonlinear Dynam 111(10):9629–9647. https://doi.org/10.1007/s11071-023-08331-y

    Article  MATH  Google Scholar 

  14. Wang X, Gao S (2020) Image encryption algorithm for synchronously updating Boolean networks based on matrix semi-tensor product theory. Inf Sci 507:16–36. https://doi.org/10.1016/j.ins.2019.08.041

    Article  MathSciNet  MATH  Google Scholar 

  15. Zhang X, Tian J (2022) Multiple-image encryption algorithm based on genetic central dogma. Phys Scr 97(5):55213. https://doi.org/10.1088/1402-4896/ac66a1

    Article  MATH  Google Scholar 

  16. Wang X, Liu C, Jiang D (2021) A novel triple-image encryption and hiding algorithm based on chaos, compressive sensing and 3D DCT. Inf Sci 574:505–527. https://doi.org/10.1016/j.ins.2021.06.032

    Article  MathSciNet  MATH  Google Scholar 

  17. Singh AK, Chatterjee K, Singh A (2023) An image security model based on chaos and DNA cryptography for IIoT images. IEEE Trans Ind Inform 19(2):1957–1964. https://doi.org/10.1109/TII.2022.3176054

    Article  MATH  Google Scholar 

  18. Li C, Tan K, Feng B, Lu J (2022) The graph structure of the generalized discrete Arnold’s cat map. IEEE Trans Comput 71(2):364–377. https://doi.org/10.1109/TC.2021.3051387

    Article  MATH  Google Scholar 

  19. Zhou W, Wang X, Wang M, Li D (2022) A new combination chaotic system and its application in a new bit-level image encryption scheme. Opt Laser Eng 149:106782. https://doi.org/10.1016/j.optlaseng.2021.106782

    Article  MATH  Google Scholar 

  20. Wang X, Zhang M (2021) An image encryption algorithm based on new chaos and diffusion values of a truth table. Inf Sci 579:128–149. https://doi.org/10.1016/j.ins.2021.07.096

    Article  MathSciNet  MATH  Google Scholar 

  21. Bao L, Tang J, Ding H, He M, Zhao L (2021) The N-level (N ≥ 4) logistic cascade homogenized mapping for image encryption. Nonlinear Dynam 105(2):1911–1935. https://doi.org/10.1007/s11071-021-06688-6

    Article  MATH  Google Scholar 

  22. Wu Y, Zhang L, Berretti S, Wan S (2023) Medical image encryption by content-aware DNA computing for secure healthcare. IEEE Trans Ind Inform 19(2):2089–2098. https://doi.org/10.1109/TII.2022.3194590

    Article  MATH  Google Scholar 

  23. Zheng W, Yan L, Gou C, Wang F (2022) An ACP-based parallel approach for color image encryption using redundant blocks. IEEE Trans Cybernetics 52(12):13181–13196. https://doi.org/10.1109/TCYB.2021.3105568

    Article  MATH  Google Scholar 

  24. Yildirim M (2022) Optical color image encryption scheme with a novel DNA encoding algorithm based on a chaotic circuit. Chaos Solitons Fractals 155:111631. https://doi.org/10.1016/j.chaos.2021.111631

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MATH  Google Scholar 

  26. Huang Z, Zhou N (2022) Image encryption scheme based on discrete cosine Stockwell transform and DNA-level modulus diffusion. Opt Laser Technol 149:107879. https://doi.org/10.1016/j.optlastec.2022.107879

    Article  MATH  Google Scholar 

  27. Zhang Q, Han J (2021) A novel color image encryption algorithm based on image hashing, 6D hyperchaotic and DNA coding. Multimed Tools Appl 80(9):13841–13864. https://doi.org/10.1007/s11042-020-10437-z

    Article  MATH  Google Scholar 

  28. Gong L, Du J, Wan J, Zhou N (2021) Image encryption scheme based on block scrambling, closed-loop diffusion, and DNA molecular mutation. Secur Commun Netw 2021:1–16. https://doi.org/10.1155/2021/6627005

    Article  MATH  Google Scholar 

  29. Jain K, Aji A, Krishnan P (2021) Medical image encryption scheme using multiple chaotic maps. Pattern Recognit Lett 152:356–364. https://doi.org/10.1016/j.patrec.2021.10.033

    Article  MATH  Google Scholar 

  30. Wang X, Guan N, Yang J (2021) Image encryption algorithm with random scrambling based on one-dimensional logistic self-embedding chaotic map. Chaos Solitons Fractals 150:111117. https://doi.org/10.1016/j.chaos.2021.111117

    Article  MathSciNet  MATH  Google Scholar 

  31. Midoun MA, Wang X, Talhaoui MZ (2021) A sensitive dynamic mutual encryption system based on a new 1D chaotic map. Opt Laser Eng 139:106485. https://doi.org/10.1016/j.optlaseng.2020.106485

    Article  MATH  Google Scholar 

  32. Briggs K (1990) An improved method for estimating Liapunov exponents of chaotic time series. Phys Lett A 151(1–2):27–32

    Article  MathSciNet  MATH  Google Scholar 

  33. Gottwald GA, Melbourne I (2009) On the implementation of the 0–1 test for chaos. SIAM J Appl Dyn Syst 8(1):129–145. https://doi.org/10.1137/080718851

    Article  MathSciNet  MATH  Google Scholar 

  34. Watson JD, Crick FHC (1953) Molecular structure of nucleic acids: a structure for deoxyribose nucleic acid. Nature 269(15):737–738. https://doi.org/10.1038/171737a0

    Article  MATH  Google Scholar 

  35. Zhang X, Tian J (2022) Fast DNA encoding algorithm inspired by the SPOOLing system. Med Biol Eng Comput 60(9):2707–2720. https://doi.org/10.1007/s11517-022-02634-9

    Article  MATH  Google Scholar 

  36. Zheng J, Feng Y, Bai C, Zhang J (2021) Hyperspectral image classification using mixed convolutions and covariance pooling. IEEE T Geosci Remote 59(1):522–534. https://doi.org/10.1109/TGRS.2020.2995575

    Article  MATH  Google Scholar 

  37. Tang X et al (2021) Hyperspectral image classification based on 3-D octave convolution with spatial–spectral attention network. IEEE T Geosci Remote 59(3):2430–2447. https://doi.org/10.1109/TGRS.2020.3005431

    Article  MATH  Google Scholar 

  38. Jiang L, Niu T, Xu Z, Xu Y (2015) Integrating encryption and marking for remote sensing image based on orthogonal decomposition. IEEE J-STARS 8(5):2232–2239. https://doi.org/10.1109/JSTARS.2015.2412691

    Article  MATH  Google Scholar 

  39. Wang X, Liu L, Song M (2023) Remote sensing image and multi-type image joint encryption based on NCCS. Nonlinear Dynam 111(15):14537–14563. https://doi.org/10.1007/s11071-023-08578-5

    Article  Google Scholar 

  40. Man Z, Li J, Di X, Zhang R, Li X, Sun X (2023) Research on cloud data encryption algorithm based on bidirectional activation neural network. Inform Sci 622:629–651. https://doi.org/10.1016/j.ins.2022.11.089

    Article  MATH  Google Scholar 

  41. Gan Z, Chai X, Han D, Chen Y (2019) A chaotic image encryption algorithm based on 3-D bit-plane permutation. Neural Comput Appl 31(11):7111–7130. https://doi.org/10.1007/s00521-018-3541-y

    Article  MATH  Google Scholar 

  42. Wu Y, Noonan JP, Agaian S (2011) NPCR and UACI randomness tests for image encryption. Cyber J Multidiscip J Sci Technol J Sel Areas Telecommun (JSAT) 2011:31–38

    MATH  Google Scholar 

  43. Shahna KU (2023) Novel chaos-based cryptosystem using four-dimensional hyperchaotic map with efficient permutation and substitution techniques. Chaos Solitons Fractals 170:113383. https://doi.org/10.1016/j.chaos.2023.113383

    Article  MathSciNet  MATH  Google Scholar 

  44. Xian Y, Wang X, Yan X, Li Q, Wang X (2020) Image encryption based on chaotic sub-block scrambling and chaotic digit selection diffusion. Opt Laser Eng 134:106202. https://doi.org/10.1016/j.optlaseng.2020.106202

    Article  MATH  Google Scholar 

  45. Wang X, Zhao M (2021) An image encryption algorithm based on hyperchaotic system and DNA coding. Opt Laser Technol 143:107316. https://doi.org/10.1016/j.optlastec.2021.107316

    Article  MATH  Google Scholar 

  46. Gao X, Mou J, Xiong L, Sha Y, Yan H, Cao Y (2022) A fast and efficient multiple images encryption based on single-channel encryption and chaotic system. Nonlinear Dynam 108(1):613–636. https://doi.org/10.1007/s11071-021-07192-7

    Article  MATH  Google Scholar 

  47. Liu P, Wang X, Su Y (2023) Image encryption via complementary embedding algorithm and new spatiotemporal chaotic system. IEEE Trans Circuits Syst Video Technol 33(5):2506–2518. https://doi.org/10.1109/TCSVT.2022.3222559

    Article  MATH  Google Scholar 

  48. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612. https://doi.org/10.1109/TIP.2003.819861

    Article  MATH  Google Scholar 

  49. Huang S et al (2022) High-quality visually secure image cryptosystem using improved Chebyshev map and 2D compressive sensing model. Chaos, Solitons Fractals 163:112584. https://doi.org/10.1016/j.chaos.2022.112584

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 91948303).

Funding

National Natural Science Foundation of China, 91948303.

Author information

Authors and Affiliations

Authors

Contributions

JT Conceptualization, Methodology, Software, Data curation and Investigation. ML Data curation and Investigation. XZ Supervision, Methodology and Reviewing. SJ, DS and SY Supervision, Reviewing.

Corresponding author

Correspondence to Shaowu Yang.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

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

Tian, J., Zhang, X., Liu, M. et al. Remote sensing image encryption algorithm based on DNA convolution. J Supercomput 81, 566 (2025). https://doi.org/10.1007/s11227-025-06982-9

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11227-025-06982-9

Keywords