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Hyperchaotic memristive ring neural network and application in medical image encryption

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Abstract

Neural networks are favored by academia and industry because of their diversity of dynamics. However, it is difficult for ring neural networks to generate complex dynamical behaviors due to their special structure. In this paper, we present a memristive ring neural network (MRNN) with four neurons and one non-ideal flux-controlled memristor. The memristor is used to describe the effect of external electromagnetic radiation on neurons. The chaotic dynamics of the MRNN is investigated in detail by employing phase portraits, bifurcation diagrams, Lyapunov exponents and attraction basins. Research results show that the MRNN not only can generate abundant chaotic and hyperchaotic attractors but also exhibits complex multistability dynamics. Meanwhile, an analog MRNN circuit is experimentally implemented to verify the numerical simulation results. Moreover, a medical image encryption scheme is constructed based on the MRNN from a perspective of practical engineering application. Performance evaluations demonstrate that the proposed medical image cryptosystem has several advantages in terms of keyspace, information entropy and key sensitivity, compared with cryptosystems based on other chaotic systems. Finally, hardware experiment using the field-programmable gate array (FPGA) is carried out to verify the designed cryptosystem.

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Acknowledgements

This work is supported by the Major Research Project of the National Natural Science Foundation of China (91964108), the National Natural Science Foundation of China (61971185, 62101182), The Natural Science Foundation of Hunan Province (2020JJ4218), the China Postdoctoral Science Foundation (2020M682552) and the Scientific Research Project of Hunan Provincial Department of Education (21C0200).

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Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Hairong Lin & Chunhua Wang

  2. School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China

    Li Cui

  3. School of Engineering and Computer Science, University of Hertfordshire, Hatfield, AL10 9AB, UK

    Yichuang Sun

  4. College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China

    Xin Zhang

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

    Wei Yao

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  1. Hairong Lin
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  2. Chunhua Wang
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  3. Li Cui
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  4. Yichuang Sun
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  5. Xin Zhang
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Correspondence to Chunhua Wang.

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Lin, H., Wang, C., Cui, L. et al. Hyperchaotic memristive ring neural network and application in medical image encryption. Nonlinear Dyn 110, 841–855 (2022). https://doi.org/10.1007/s11071-022-07630-0

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