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Pseudorandom number generator based on a 5D hyperchaotic four-wing memristive system and its FPGA implementation

PRNG based on a 5D hyperchaotic four-wing memristive system and its FPGA implementation

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A Correction to this article was published on 24 June 2021

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Abstract

Pseudorandom numbers are widely used in information encryption, spread spectrum communication and other science and technology and engineering fields. Because chaos is very sensitive to the initial conditions and has good inherent pseudo-random characteristics, the research of pseudorandom number generator (PRNG) based on a chaotic system becomes a new beneficial exploration. This paper presents a FPGA PRNG based on a 5D hyperchaotic four-wing memristive system (HFWMS). The 5D HFWMS has multiline equilibrium and three positive Lyapunov exponents, which indicates that the system has very complex dynamic behavior. On this basis, a FPGA PRNG based on the 5D HFWMS is proposed. The proposed PRNG is implemented in VHDL language, modeled and simulated on Vivado 2018.3 platform, and synthesized by FPGA device ZYNQ-XC7Z020 on Xilinx. The post-processing module consists of 16 linear shift registers and 15 levels XOR chain. The maximum operating frequency is 138.331 MHz and the speed is 15.37 Mbit/s. The random bit sets generated by PRNG are further verified by NIST 800.22 statistical standard. The security is analyzed by dynamic degradation, keyspace, key sensitivity and correlation. Experiments show that the design can be applied to various embedded password applications.

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References

  1. N. Liao, Y. Song, S. Su et al., J. Intell. Fuzzy Syst. 39, 433–447 (2020)

    Google Scholar 

  2. Z. Xia, Z. Fang, F. Zou F et al., Secur Commun Netw 2019, 6956072 (2019)

    Google Scholar 

  3. K. Gu, W.B. Zhang, S.J. Lim et al., IEEE Trans. Cloud Comput. (2020). https://doi.org/10.1109/TCC.2020.2985050

    Article  Google Scholar 

  4. Z. Fang, J. Cai and L. Tian, Comp. Syst. Sci. Eng. 35, 299–305 (2020)

  5. J. Zuo, Y. Lu, H. Gao et al., Computer. Mater. Continua 65, 683–704 (2020)

  6. A. Kelec, Z. Djuric, Comp. Syst. Sci. Eng. 35, 271–282 (2020)

  7. F. Yu, Z. Zhang, H. Shen et al., Front. Phys. 9, 690651 (2021)

  8. F. Yu, L. Li, Q. Tang et al., Discrete Dyn. Nat. Soc. 2019, 2545123 (2019)

    Google Scholar 

  9. F. Yu, S. Qian, X. Chen et al., Complexity 2021, 6683284 (2021)

  10. X. Chen, S. Qian, F. Yu et al., Complexity 2020, 8274685 (2020)

  11. M. Itoh, Int. J. Bifurc. Chaos 9, 155–213 (1999)

    Google Scholar 

  12. C. Guyeux, R. Couturier, P.C. Heam et al., J. Supercomput. 71, 3877–3903 (2015)

    Google Scholar 

  13. Y. Wang, Z. Liu, J. Ma et al., Nonlinear Dyn. 83, 2373–2391 (2016)

    Google Scholar 

  14. F. Yu, L. Liu, L. Xiao et al., Neurocomputing 350, 108–116 (2019)

    Google Scholar 

  15. S. A. Sariman, I. Hashim, Computer. Mater. Continua 65, 69–85 (2020)

  16. F. Wang, L. Zhang, S. Zhou et al., Neurocomputing 362, 195–202 (2019)

    Google Scholar 

  17. H. Lin, C. Wang, W. Yao, Y. Tan, Commun. Nonlinear Sci. Numer. Simul. 90, 105390 (2020)

    MathSciNet  Google Scholar 

  18. W. Yao, C. Wang, Y. Sun et al., IEEE Trans. Syst. Man, Cybernetics: Syst. (2020). https://doi.org/10.1109/TSMC.2020.2997930

  19. L. Zhou, F. Tan, F. Yu et al., Neurocomputing 359, 264–75 (2019)

    Google Scholar 

  20. W. Yao, C. Wang, J. Cao et al., Neurocomputing 363, 281–294 (2019)

    Google Scholar 

  21. C. Zhou, C. Wang, Y. Sun et al., Neurocomputing 403, 211–223 (2020)

    Google Scholar 

  22. W. Yao, C.H. Wang, Y.C. Sun et al., Neurocomputing 404, 367–380 (2020)

    Google Scholar 

  23. F. Yu, Z. Zhang, L. Liu et al., Complexity 2020, 5859273 (2020)

    Google Scholar 

  24. L. Zhou, F. Tan, F. Yu, IEEE Syst. J. 14, 2508–2519 (2020)

    ADS  Google Scholar 

  25. Q. Lai, B. Norouzi, F. Liu, Chaos Solitons Fractals 114, 230–245 (2018)

    ADS  MathSciNet  Google Scholar 

  26. J. Deng, M. Zhou, C. Wang et al., Multimedia Tools Appl. 80, 13821–13840 (2021)

  27. J. Zeng, C H. Wang, Secur. Commun. Netw. 2021, 6675565 (2021)

  28. B. Lu, F. Liu, X. Ge et al., Computer. Mater. Continua 61, 687–699 (2019)

  29. J. Liu, J. Li, J. Cheng et al., Computer. Mater. Continua 61, 889–910 (2019)

  30. F. Yu, L. Liu, H. Shen et al., Math. Probl. Eng. 2020, 7530976 (2020)

    Google Scholar 

  31. Q.L. Deng, C.H. Wang, L.M. Yang, Int. J. Bifurc. Chaos 30, 2050086 (2020)

    Google Scholar 

  32. F. Yang, J. Mou, C. Ma et al., Opt. Lasers Eng. 129, 106031 (2020)

  33. Q. Lai, Z. Wan, P.D.K. Kuate, Electron. Lett. (2020). https://doi.org/10.1049/el.2020.1630

    Article  Google Scholar 

  34. H. Lin, C. Wang, F. Yu et al., IEEE Trans. Industrial Electron. (2020). https://doi.org/10.1109/TIE.2020.3047012

  35. L. Cui, M. Lu, Q. Ou et al., Chaos Solitons Fractals 138, 109894 (2020)

    MathSciNet  Google Scholar 

  36. G. Cheng, C. Wang, C. Xu et al., Multimedia Tools Appl. 79, 29243–29263 (2020)

  37. M. Bucolo, R. Caponetto, L. Fortuna et al., IEEE Circuits Syst. Mag. 2, 4–19 (2002)

    Google Scholar 

  38. H.P. Hu, L.F. Liu, N.D. Ding, Comput. Phys. Commun. 184, 765–768 (2013)

    ADS  MathSciNet  Google Scholar 

  39. V. Lynnyk, N. Sakamoto, S. Celikovsky, IFAC-Papers OnLine 48, 257–261 (2015)

    Google Scholar 

  40. Z. Hua, Y. Zhou, IEEE Trans. Syst. Man Cybern. Syst. (2019) https://doi.org/10.1109/TSMC.2019.2932616

  41. Z. Hua, Y. Zhang, Y. Zhou, IEEE Trans. Signal Process. 68, 1937–1949 (2020)

    ADS  MathSciNet  Google Scholar 

  42. Z. Hua, B. Zhou, Y. Zhou, IEEE Trans. Ind. Electron. 65, 2557–2566 (2018)

    Google Scholar 

  43. M.O. Meranza-Castillon, M.A. Murillo-Escobar, R.M. Lopez-Gutierrez et al., AEU Int. J. Electron. Commun. 107, 239–251 (2019)

    Google Scholar 

  44. A. Akhshani, A. Akhavan, A. Mobaraki et al., Commun. Nonlinear Sci. Numer. Simul. 19, 101–111 (2014)

    ADS  Google Scholar 

  45. Y. Qi, K. Sun, H. Wang et al., Comput. Eng. Appl. 53, 135–139 (2017)

    Google Scholar 

  46. F. Yang, J. Mou, J. Liu et al., Signal Process. 169, 107373 (2020)

    Google Scholar 

  47. J. Sun, M. Peng, F. Liu et al., Complexity 2020, 8815315 (2020)

    Google Scholar 

  48. X. Ye, J. Mou, C. Luo et al., Nonlinear Dyn. 92, 923–933 (2018)

    Google Scholar 

  49. H. Lin, C. Wang, Y. Tan, Nonlinear Dyn. 99, 2369–2386 (2020)

    Google Scholar 

  50. Y. Liu, X. Tong, IET Inf. Secur. 10, 433–441 (2016)

    Google Scholar 

  51. K. Wang, Q. Yan, S. Yu et al., VLSI Des. 2014, 923618 (2014)

    Google Scholar 

  52. D. Strukov, G. Snider, D. Stewart et al., Nature 453, 80–83 (2008)

    ADS  Google Scholar 

  53. Q. Lai, Z. Wan, P.D.K. Kuate et al., Commun. Nonlinear Sci. Numer. Simul. 89, 105341 (2020)

    MathSciNet  Google Scholar 

  54. S. Zhong, Computer. Mater. Continua 60, 465–479 (2019)

  55. H. Lin, C. Wang, Y. Sun et al., Nonlinear Dyn. 100, 3667–3683 (2020)

  56. F. Yu, L. Liu, H. Shen et al., Complexity 2020, 5904607 (2020)

    Google Scholar 

  57. F. Yu, S. Qian, X. Chen et al., Int. J. Bifurc. Chaos 30, 2050147 (2020)

    Google Scholar 

  58. F. Yu, L. Liu, S. Qian et al., Complexity 2020, 8034196 (2020)

    Google Scholar 

  59. F. Yu, L. Li, B. He et al., IEEE Access 7, 181884–181898 (2019)

    Google Scholar 

  60. F. Yu, L. Liu, B. He et al., Complexity 2019, 4047957 (2019)

  61. C. Wannaboon, M. Tachibana, W. San-Um, Chaos 28, 063126 (2018)

    ADS  Google Scholar 

  62. F. Pareschi, G. Setti, R. Rovatti, IEEE Trans. Circuits Syst. I Regul Papers 57, 3124–3137 (2010)

    MathSciNet  Google Scholar 

  63. S. Zhou, W. Zhang, N. Wu, Solid-State Electron. 52, 233–238 (2008)

    ADS  Google Scholar 

  64. F. Yu, L. Gao, L. Liu et al., Wirel. Pers. Commun. 111, 843–851 (2020)

    Google Scholar 

  65. F. Yu, Wirel. Pers. Commun. 78, 905–914 (2014)

    Google Scholar 

  66. F. Yu, Q. Tang, W. Wang et al., Wirel. Pers. Commun. 86, 671–681 (2016)

    Google Scholar 

  67. J. Danger, S. Guilley, P. Hoogvorst, Microelectron. J. 40, 1650–1656 (2009)

    Google Scholar 

  68. V. Guglielmi, P. Pinel, D. Fournier-Prunaret et al., Chaos Solitons Fractals 42, 2135–2144 (2009)

    ADS  Google Scholar 

  69. Q. Luo, J. Zhan, Microelectron. Comput. (2009). https://doi.org/10.1360/972009-1549

    Article  Google Scholar 

  70. A. Rezk, A. Madian, A. Radwan et al., AEU Int. J. Electron. Commun. 98, 174–180 (2019)

    Google Scholar 

  71. M. Garcia-Bosque, A. Perez-Resa, C. Sanchez-Azqueta et al., IEEE Trans. Instrum. Meas. 68, 291–293 (2018)

    Google Scholar 

  72. L. Merah, A. Ali-Pacha, N. Said et al., Appl. Math. Sci. 7, 2719–2734 (2013)

    MathSciNet  Google Scholar 

  73. I. Koyuncu, A. Ozcerit, Comput. Electr. Eng. 58, 203–214 (2017)

    Google Scholar 

  74. A. Akgul, H. Calgan, I. Koyuncu et al., Nonlinear Dyn. 84, 481–495 (2016)

    Google Scholar 

  75. Z. Wang, A. Akgul, V. Pham et al., Nonlinear Dyn. 89, 1877–1887 (2017)

    Google Scholar 

  76. I. Koyuncu, M. Tuna, I. Pehlivan et al., Analog Integr. Circuits Signal Process. 102, 445–456 (2020)

    Google Scholar 

  77. J. Zhang, W. Wang, X. Wang et al., J. Comput. Sci. Technol. 32, 329–339 (2017)

    Google Scholar 

  78. M. Bucolo, A. Buscarino, C. Famoso et al., Nonlinear Dyn. 98, 2989–2999 (2019)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grants 61504013, 61702052 and 61901169, and by the Natural Science Foundation of Hunan Province under Grants 2019JJ50648, 2020JJ4622 and 2019JJ40190, and by Guangxi Key Laboratory of Cryptography and Information Security under Grant GCIS201919, and by the Postgraduate Training Innovation Base Construction Project of Hunan Province under Grant 2020-172-48, and the Postgraduate Scientific Research Innovation Project of Hunan Province under Grant CX20200884, and by the Scientific Research Fund of Hunan Provincial Education Department under grant 18A137, and by the young teacher development program project of Changsha university of science and technology under grant 2019QJCZ013.

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Authors and Affiliations

  1. School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410114, China

    Fei Yu, Lixiang Li, Binyong He, Li Liu, Shuai Qian, Zinan Zhang, Hui Shen & Shuo Cai

  2. Guangxi Key Laboratory of Cryptography and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China

    Fei Yu

  3. Hunan Post and Telecommunication Planning and Designing Institute, No. 236 Yuanda Road, Changsha, 410126, China

    Yi Li

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  1. Fei Yu
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Correspondence to Fei Yu.

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Yu, F., Li, L., He, B. et al. Pseudorandom number generator based on a 5D hyperchaotic four-wing memristive system and its FPGA implementation. Eur. Phys. J. Spec. Top. 230, 1763–1772 (2021). https://doi.org/10.1140/epjs/s11734-021-00132-x

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