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An Improved Digital Image Encryption Algorithm Based on Sine Compound Chaotic System

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Image and Graphics (ICIG 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12888))

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Abstract

The rapid development of digital image transmission technology requires a more secure and effective image encryption scheme to provide the necessary security. This paper introduces an improved sine-transform-based chaotic system (ISTBCS). By linearly weighting and nonlinearly multiplying the selected classic maps, the new chaotic maps with more complex dynamics are obtained through sinusoidal transformation. Performance evaluation shows that it has chaotic characteristics such as wide range of chaos, high complexity, and strong non-periodicity. On this basis, an image encryption algorithm that uses bidirectional pixel encoding, displacement and diffusion at the same time is designed. By pixel encoding the plaintext, the small changes in the ordinary image can be propagated to all the pixels of the encrypted image, which greatly improves the ability to resist known plaintext attacks and selected plaintext attacks. Simulation results and performance analysis show that the algorithm has a large key space, strong key sensitivity, strong performance to make the structural data correlation disappear, and then can increase the entropy, has good anti attack ability, and can effectively meet the needs of image encryption.

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References

  1. Wen, H.P.: Image encryption scheme based on quantum and spatiotemporal chaos. J. Hefei Univ. Technol. (Nat. Sci. Ed.) 43(06), 777–783 (2020)

    MATH  Google Scholar 

  2. Cao, G.H.: Image scrambling method based on logistic uniform distribution. Acta Phys. Sin. 60(11), 133–140 (2011)

    Google Scholar 

  3. Tian, X.P.: Sine transform chaotic system and performance analysis. J. Xi’an Univ. Posts Telecommun. 23(06), 37–43 (2018)

    Google Scholar 

  4. Hua, Z.Y.: Cosine-transform-based chaotic system for image encryption. Inform. Sci. 480, 403–419 (2019)

    Article  Google Scholar 

  5. Fang, J.: An image encryption algorithm based on chaotic encryption and DNA encoding. Acta Phys. Sin.,1–22 (2021)

    Google Scholar 

  6. Chen, W.: General image encryption algorithm based on deep learning compressed sensing and compound chaotic system. Acta Phys. Sin. 69(24), 99–111 (2020)

    Google Scholar 

  7. 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(4), 2693–2721 (2019). https://doi.org/10.1007/s11071-019-05157-5

    Article  MATH  Google Scholar 

  8. Liu, Y., Qin, Z., Liao, X., Wu, J.: Cryptanalysis and enhancement of an image encryption scheme based on a 1-D coupled Sine map. Nonlinear Dyn. 100(3), 2917–2931 (2020). https://doi.org/10.1007/s11071-020-05654-y

    Article  Google Scholar 

  9. Hu, Y.C.: An image encryption algorithm security analysis based on compound chaotic sequence. Comput. Appl. Res. 1–8 (2021)

    Google Scholar 

  10. Zhong, Y.R.: Image encryption algorithm based on 2D Chebyshev-Sine mapping. J. Zhejiang Univ. (Sci. Ed.) 1008–9497(2019)

    Google Scholar 

  11. Chen, S.: Image encryption algorithm based on chaotic system and artificial neural network. Comput. Syst. Appl. 29(08), 236–241 (2020)

    Google Scholar 

  12. Rosenstein, M.T.: A practical method for calculating largest Lyapunov exponents from small data sets. Phys. D 65, 117–134 (1993)

    Article  MathSciNet  Google Scholar 

  13. Richman, J.S.: Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278, 2039–2049 (2000)

    Article  Google Scholar 

  14. Özkaynak, F.: Role of NPCR and UACI tests in security problems of chaos based image encryption algorithms and possible solution proposals. In: 2017 International Conference on Computer Science and Engineering (UBMK), pp. 621–624. IEEE (2017)

    Google Scholar 

  15. Khedmati, Y.: 2D Hybrid chaos map for image security transform based on framelet and cellular automata. Inform. Sci. 512, 855–875 (2020)

    Article  MathSciNet  Google Scholar 

  16. Wang, X.Y.: A color image encryption with heterogeneous bit-permutation and correlated chaos. Opt. Commun. 342, 51–60 (2015)

    Article  Google Scholar 

  17. Aboughalia, R.A.: Color image encryption based on chaotic block permutation and XOR operation. In: Libyan International Conference on Electrical Engineering and Technologies (LICEET) (2018)

    Google Scholar 

  18. Li, S., Ding, W., Yin, B., Zhang, T., Ma, Y.: A novel delay linear coupling logistics map model for color image encryption. Entropy 20(6), 463 (2018). https://doi.org/10.3390/e20060463

    Article  Google Scholar 

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Acknowledgement

This work is financially supported by National Natural Science Foundation of China (No. 61072079/61461053).

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Authors and Affiliations

  1. Information School, Yunnan University, Kunming, 650500, China

    Jianchao Tang, Liyong Bao, Hongwei Ding, Zheng Guan & Min He

Authors
  1. Jianchao Tang
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  2. Liyong Bao
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  3. Hongwei Ding
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  4. Zheng Guan
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  5. Min He
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Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Tsinghua University, Beijing, China

    Shi-Min Hu

  3. Tampere University, Tampere, Finland

    Moncef Gabbouj

  4. Zhejiang University, Hangzhou, China

    Kun Zhou

  5. Technion – Israel Institute of Technology, Haifa, Israel

    Michael Elad

  6. Tsinghua University, Beijing, China

    Kun Xu

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Tang, J., Bao, L., Ding, H., Guan, Z., He, M. (2021). An Improved Digital Image Encryption Algorithm Based on Sine Compound Chaotic System. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12888. Springer, Cham. https://doi.org/10.1007/978-3-030-87355-4_56

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  • DOI: https://doi.org/10.1007/978-3-030-87355-4_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87354-7

  • Online ISBN: 978-3-030-87355-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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