Skip to main content
Log in

A digital image encryption algorithm based on bit-planes and an improved logistic map

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

Abstract

This paper presents a digital image encryption algorithm based on bit-planes and an improved logistic map. First, a chaotic sequence, which is generated by the improved logistic map, scrambles the pixels of the original image. Second, the scrambled image is split into a high 4-bit matrix and a low 4-bit matrix. The low 4-bit matrix is then introduced into the improved logistic model to generate a chaotic sequence that is highly correlated with the image as the key, and the key is used for position scrambling and the XOR operation of the high 4-bit matrix. Finally, the two matrices are combined into an 8-bit image matrix to obtain the ciphertext image. The algorithm has a significant one-time pad characteristic. MATLAB simulation experiments are conducted to analyze the security of image encryption in terms of the histogram, plaintext sensitivity, information entropy, and adjacent pixels correlation index. Experimental results show that the number of pixel changes ratio (NPCR) is greater than 90% and the information entropy of the ciphertext image reaches 7.99, demonstrating that the algorithm offers good encryption.

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

Similar content being viewed by others

References

  1. Cao JQ, Xiao HR, Lan ZL, Zhang H (2010) Chaos encryption algorithm based on bit-plane of digital image. Computer technology and. Development 20(8):133–136

    Google Scholar 

  2. Chai XL, (2017) An image encryption algorithm based on bit level Brownian motion and new chaotic systems. Multimedia Tools & Applications 76:1159–1175

  3. Chai XL, Gan ZH (2016) New bit-level self-adaption color image encryption algorithm based on Hyperchaotic system. Comput Sci 43(4):134–139

    Google Scholar 

  4. Chen S, Yang YJ, Yin X (2015) Digital image encryption algorithm based on improved Knight's tour and bit operation. J Chin Comput Syst 36(7):1607–1612

    Google Scholar 

  5. Deng XH, Liao CL, Zhu CX, Chen ZG (2014) Image encryption algorithms based on chaos through dual scrambling of pixel position and bit. J Commun, 35(3):216–223

  6. Guo Y, Shao LP, Lu Y (2015) Bit-level image encryption algorithm based on Josephus and Henon chaotic map. Appl Res Comput 32(4):1131–1137

    Google Scholar 

  7. Hao M (2015) Image encryption algorithm based on multiple ChaoticSystems and bit operations. Res Explor Lab 34(3):35–39

    Google Scholar 

  8. Hao L, Min L (2014) Statistical tests and chaotic synchronization based pseudorandom number generator for string bit sequences with application to image encryption. Eur Phys J Spec Top 223(8):1679–1697

    Article  Google Scholar 

  9. Huang FZ, Zhao Y, Liang NX (2017) A method for real-time monitoring and evaluating asphalt mixture paving uniformity based on digital image processing technology. J Highway Transp Res Dev 34(4):8–15

    Google Scholar 

  10. Khanzadi H, Eshghi M, Borujeni SE (2014) Image encryption using random bit sequence based on chaotic maps. Arab J Sci Eng 39(2):1039–1047

    Article  Google Scholar 

  11. Li B, Liao XF, Jiang Y (2017) A novel image encryption scheme based on logistic map and dynatomic modular curve. Multimed Tools Appl (1):1–28. https://doi.org/10.1007/s11042-017-4786-7

  12. Liang W, Tang MD, Jing L, Sangaiah AK, Huang Y (2017) SIRSE: a secure identity recognition scheme based on electroencephalogram data with multi-factor feature. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng. 2017.05.001

  13. Liao X, Guo SJ, Yin JJ, Wang H, Li X, Sangaiah AK (2017) New cubic reference table based image steganography. Multimed Tools Appl, (4):1–18. https://doi.org/10.1007/s11042-017-4946-9

  14. Liu R (2015) New algorithm for color image encryption using improved 1D logistic. Open Cybern Systemics J 9(1):210–216

    Article  Google Scholar 

  15. Liu LP, Zhang XF (2013) Image encryption algorithm based on chaos and bit operations. J Comput Appl 33(4):1070–1073

    Google Scholar 

  16. Liu Y, Tong XJ, Ma J (2016) Image encryption algorithm based on hyper-chaotic system and dynamic S-box. Multimed Tools Appl 75(13):7739–7759

    Article  Google Scholar 

  17. Lu P, Dong H, Ma X (2011) Image scrambling optimization algorithm based on mixed chaos system and bit decomposition. Comput Eng Appl 47(21):191–194

    Google Scholar 

  18. Pan TG, Li D (2013) A bit transformation image encryption algorithm based on chaotic map. Electric Mach Control 17(10):97–100

    Google Scholar 

  19. Hu PF, Ning HS, Qiu T, Xu Y, Luo X, Sangaiah AK (2017) A unified face identification and resolution scheme using cloud computing in internet of things. Futur Gener Comput Syst, doi:https://doi.org/10.1016/j.future.2017.03.030

  20. Samuel OW, Zhou H, Li XX, Wang H, Zhang HS, Sangaiah AK, Li GL (2017) Pattern recognition of electromyography signals based on novel time domain features for amputees' limb motion classification. Comput Electr Eng, 1–10. https://doi.org/10.1016/j.compeleceng.2017.04.003

  21. Samuel OW, Asogbon GM, Sangaiah AK, Li GL (2017) Multi-technique object tracking approach- a reinforcement paradigm. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2017.02.002

  22. Shi LW, Wang DY (2017) Evalution indexes of asphalt mixture main skeleton based on digital image processing. China J Highway Transport 30(5):52–58

    Google Scholar 

  23. Tuo C, Qin Z, Li Q (2013) Color image encryption algorithm based on 2D logistic map and bit rear range. Comput Sci 40(8):300–302

    Google Scholar 

  24. XH W (2013) Research on the bit-level image encryption algorithm based on chaos. Microelectronics Comput 12:69–72

    Google Scholar 

  25. Xie GB, Wang T (2016) A chaotic image encryption algorithm based on pixel scrambling and bit substitution. Microelectronics Comput 33(3):80–85

    Google Scholar 

  26. Xu C, Zhang XF (2014) Improved image encryption algorithm based on bit-plane. Comput Eng Des 35(2):451–456

    Google Scholar 

  27. Ye GD, Huang XL (2016) A novel block chaotic encryption scheme for remote sensing image. Multimed Tools Appl 75(18):1–14

    Article  Google Scholar 

  28. Yuan L, Kang BS (2009) Image scrambling algorithm based on logistic chaotic sequence and bit exchange. J Comput Appl 29(10):2681–2683

    Google Scholar 

  29. Zhang YQ, Wang XY (2014) Analysis and improvement of a chaos-based symmetric image encryption scheme using a bit-level permutation. Nonlinear Dyn 77(3):687–698

    Article  Google Scholar 

  30. Zhang R, Shen J, Wei F, Li X, Sangaiah AK (2017) Medical image classification based on multi-scale non-negative sparse coding. Artif Intell Med. https://doi.org/10.1016/j.artmed.2017.05.006

  31. Zhang GS, Chen DS, Qiu HT, LingHu D, Wang HY (2017) Design of High Speed Image Tracking System Based on FPGA. Microelectronics Comput 34(4):13–16

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Project of the National Science & Technology Pillar Program of China during the Twelfth Five-year Plan Period (2015BAK27B03) and the Science & Technology Cooperation Project of Guizhou (LH-2015-7294).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shiqiang Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Yang, D., Zhou, H. et al. A digital image encryption algorithm based on bit-planes and an improved logistic map. Multimed Tools Appl 77, 10217–10233 (2018). https://doi.org/10.1007/s11042-017-5406-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-5406-2

Keywords

Navigation