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2D sine-logistic-tent-coupling map for image encryption

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Abstract

With the development of chaotic image encryption technology, chaotic system is increasingly at the core of cryptography, a good performance of the chaotic system is very important for the whole encryption algorithm. Some existing two-dimensional chaotic systems have the risk of small key space and are easy to crack. Based on this, a new two-dimensional sine-logistic-tent-coupled mapping chaotic system is proposed, and the encryption algorithm is designed on this basis. The performance analysis shows that the chaotic mapping has better chaotic behavior than the existing two-dimensional chaotic mapping. Overall, image encryption includes scrambling and diffusion of two steps. Based on the traditional zigzag scrambling, authors use the two-way zigzag traversal to disturb the whole image to reduce the correlation between pixels, which has achieved good results. And the use of pixel-level diffusion operation makes the whole image completely chaotic. In addition, the key used in the encryption process is related to the plaintext image, which further enhances the security of the encryption algorithm. Simulation results and security analysis show that the encryption algorithm has high-security performance and can resist external attacks.

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References

  • Abbasi AA, Mazinani M, Hosseini R (2021) Evolutionary-based image encryption using biomolecules and non-coupled map lattice. Opt Laser Technol 140(9):106974

    Article  Google Scholar 

  • Ahmad J, Hwang SO (2015) Chaos-based diffusion for highly autocorrelated data in encryption algorithms. Nonlinear Dyn 82(4):1839–1850

    Article  MathSciNet  MATH  Google Scholar 

  • Ahmad I, Shin S (2021) A novel hybrid image encryption–compression scheme by combining chaos theory and number theory. Signal Process 98:116418

    Google Scholar 

  • Aqeel-ur-Rehman LX, Hahsmi MA, Haider R (2018) An efficient mixed inter-intra pixels substitution at 2bits-level for image encryption technique using DNA and chaos. Optik Int J Light Electron Opt 153:117–134

    Article  Google Scholar 

  • Azam NA, Hayat U, Ayub M (2021) A substitution box generator, its analysis, and applications in image encryption. Signal Process 187:108144

    Article  Google Scholar 

  • Chai X, Gan Z, Yang K, Chen Y, Liu X (2017) An image encryption algorithm based on the memristive hyperchaotic system, cellular automata and DNA sequence operations. Signal Process: Image Commun 52:6–19

    Google Scholar 

  • Chai X, Zhi X, Gan Z, Zhang Y, Chen Y, Fu J (2021) Combining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption. Signal Process 183(9):108041

    Article  Google Scholar 

  • Dong W, Li Q, Tang Y (2021) Image encryption-then-transmission combining random sub-block scrambling and loop DNA algorithm in an optical chaotic system. Chaos Solitons Fractals 153(1):111539

    Article  MathSciNet  Google Scholar 

  • Dua M, Wesanekar A, Gupta V, Bhola N, Dua S (2020) Differential evolution optimization of intertwining logistic map-DNA based image encryption technique. J Ambient Intell Hum Comput 11(10):3771–3786

    Article  Google Scholar 

  • Fridrich J (1997) Image encryption based on chaotic maps. In: 1997 IEEE International Conference on Systems Man and Cybernetics Computaional Cybernetics and Simulations, pp 1105–1110

  • Ghazvini M, Mirzadi M, Parvar N (2020) A modified method for image encryption based on chaotic map and genetic algorithm. Multimed Tools Appl 79:26927–26950

    Article  Google Scholar 

  • Grassberger P, Procaccia I (1983) Estimation of the Kolmogorov entropy from a chaotic signal. Phys Rev A 28(4):2591–2593

    Article  Google Scholar 

  • Hilborn RC (2001) Chaos and nonlinear dynamics: an introduction for scientists and engineers, 2nd edn. Oxford University Press, USA

    MATH  Google Scholar 

  • Hua Z, Zhou Y (2016) Image encryption using 2D logistic-adjusted-sine map. Inf Sci 339:237–253

    Article  Google Scholar 

  • Hua Z, Zhou Y, Pun C, Chen CLP (2015) 2D sine logistic modulation map for image encryption. Inf Sci 297:80–94

    Article  Google Scholar 

  • Hua Z, Jin F, Xu B, Huang H (2018) 2D Logistic-sine-coupling map for image encryption. Signal Process 149:148–161

    Article  Google Scholar 

  • Jia Q (2007) Hyperchaos generated from the Lorenz chaotic system and its control. Phys Lett A 366(3):217–222

    Article  MATH  Google Scholar 

  • Kadir A, Aili M, Sattar M (2017) Color image encryption scheme using coupled hyper chaotic system with multiple impulse injections. Optik 129:231–238

    Article  Google Scholar 

  • Li Y, Tang WK, Chen G (2005) Generating hyperchaos via state feedback control. Int J Bifurc Chaos 15(10):3367–3375

    Article  Google Scholar 

  • Liao X, Lai S, Zhou Q (2010) A novel image encryption algorithm based on self-adaptive wave transmission. Signal Process 90(9):2714–2722

    Article  MATH  Google Scholar 

  • Lu Z, Xin X, Chen W (2009) Digital image encryption using zigzag scan coding. Comput Eng Design 30(9):2145–2144

    Google Scholar 

  • Man Z, Li J, Di X, Sheng Y, Liu Z (2021) Double image encryption algorithm based on neural network and chaos. Chaos Solitons Fractals 152(24):111318

    Article  MathSciNet  MATH  Google Scholar 

  • Midoun MA, Wang X, Talhaoui MZ (2021) A sensitive dynamic mutual encryption system based on a new 1D chaotic map. Opt Lasers Eng 139(1):106485

    Article  Google Scholar 

  • Moon S, Baik JJ, Seo JM (2021) Chaos synchronization in generalized Lorenz systems and an application to image encryption. Commun Nonlinear Sci Numer Simul 96:105708

    Article  MathSciNet  MATH  Google Scholar 

  • Roy S, Shrivastava M, Rawat U, Pandey CV, Nayak SK (2021) IESCA: An efficient image encryption scheme using 2-D cellular automata. J Inf Secur Appl 61(5):102919

    Google Scholar 

  • Shahna KU, Mohamed A (2020) A novel image encryption scheme using both pixel level and bit level permutation with chaotic map. Applied Soft Comput 90:106162

    Article  Google Scholar 

  • 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

    Article  MathSciNet  MATH  Google Scholar 

  • Wang X, Liu P (2021) A new full chaos coupled mapping lattice and its application in privacy image encryption. IEEE Trans Circuits Syst I Regul Pap. https://doi.org/10.1109/TCSI.2021.3133318

    Article  Google Scholar 

  • Wang X, Liu C, Xu D, Liu C (2016) Image encryption scheme using chaos and simulated annealing algorithm. Nonlinear Dyn 84(3):1417–1429

    Article  MathSciNet  Google Scholar 

  • Wang X, Feng L, Zhao H (2019) Fast image encryption algorithm based on parallel computing system. Inf Sci 486:340–358

    Article  MATH  Google Scholar 

  • Wang X, Zhang H, Sun Y, Wang X (2021) A plaintext-related image encryption algorithm based on compressive sensing and a novel hyperchaotic system. Int J Bifurc Chaos 31(2):2150021

    Article  MathSciNet  MATH  Google Scholar 

  • Wei D, Jiang M (2021) A fast image encryption algorithm based on parallel compressive sensing and DNA sequence. Optik Int J Light Electron Opt 238(6):166748

    Article  Google Scholar 

  • Wolf A, Swift JB, Swinney HL, Vastano JA (1985) Determining Lyapunov exponents from a time series. Physica D 16(3):285–317

    Article  MathSciNet  MATH  Google Scholar 

  • Wu Y, Noonan JP, Agaian S (2011) NPCR and UACI randomness tests for image encryption, cyber journals: multidisciplinary journals in science and technology. J Sel Areas Telecommun 1(2):31–38

    Google Scholar 

  • Wu Y, Yang G, Jin H, NooNon JP (2012) Image encryption using the two-dimensional logistic chaotic map. J Electron Imaging 21(1):3014

    Article  Google Scholar 

  • Wu Y, Zhou Y, Saveriades G, Noonan JP, Natarajan P (2013) Local Shannon entropy measure with statistical tests for image randomness. Inf Sci 222:323–342

    Article  MathSciNet  MATH  Google Scholar 

  • Xu J, Mou J, Liu J, Hao J (2021) The image compression-encryption algorithm based on the compression sensing and fractional-order chaotic system. Vis Comput. https://doi.org/10.1007/s00371-021-02085-7

    Article  Google Scholar 

  • Zarebnia M, Parvaz R (2021) Image encryption algorithm by fractional based chaotic system and framelet transform. Chaos Solitons Fractals 152:111402

    Article  MathSciNet  MATH  Google Scholar 

  • Zhang S, Liu L (2021) A novel image encryption algorithm based on SPWLCM and DNA coding. Math Comput Simulation 190(1):723–744

    Article  MathSciNet  MATH  Google Scholar 

  • Zhang Y, Chen A, Tang Y, Dang J, Wang G (2020) Plaintext-related image encryption algorithm based on perceptron-like network. Inf Sci 526:180–202

    Article  MathSciNet  Google Scholar 

  • Zhou S (2021) A real-time one-time pad DNA-chaos image encryption algorithm based on multiple keys. Opt Laser Technol 143:107359

    Article  Google Scholar 

  • Zhou Y, Bao L, Chen CLP (2014) A new 1D chaotic system for image encryption. Signal Process 97:172–182

    Article  Google Scholar 

  • Zhu H, Zhao Y, Song Y (2019) 2D logistic-modulated-sine-coupling-logistic chaotic map for image encryption. IEEE Access 7:14081–14098

    Article  Google Scholar 

Download references

Acknowledgements

This research is supported by the National Natural Science Foundation of China (No: 61672124), the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (No: MMJJ20170203), Liaoning Province Science and Technology Innovation Leading Talents Program Project (No: XLYC1802013), Key R&D Projects of Liaoning Province (No: 2019020105-JH2/103), Jinan City ‘20 universities’ Funding Projects Introducing Innovation Team Program (No: 2019GXRC031).

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Correspondence to Nana Guan.

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We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “2D sine-logistic-tent-coupling map for image encryption”.

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Wang, X., Guan, N. 2D sine-logistic-tent-coupling map for image encryption. J Ambient Intell Human Comput 14, 13399–13419 (2023). https://doi.org/10.1007/s12652-022-03794-0

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