Three-dimensional m-HR neuron model and its application in medical image encryption

Qianqian Shi, Shaocheng Qu, Xinlei An, Ziming Wei and Chen Zhang

Chaos, Solitons & Fractals, 2024, vol. 189, issue P1

Abstract: Theoretical research on neuronal dynamics is crucial for elucidating neural functions of the human brain, and electromagnetic fields significantly influence the electrical activity of neurons. This paper proposes a flux-controlled memristor and analyzes its frequency and amplitude dependent pinched hysteresis loops. Considering the electromagnetic induction effect of the memristor, a novel memristive Hindmarsh–Rose (m-HR) neuron model is constructed, which exhibits the coexistence of asymmetric hidden attractors. The theoretical analyses and simulation results on the Hamilton energy demonstrate that the energy evolution of the m-HR neuron model is predominantly associated with state variables. Subsequently, the intricate discharge patterns of the model are investigated through one-parameter and two-parameter bifurcation analysis, accompanied by complexity assessment. Based on the model, a medical image encryption scheme is devised, capable of simultaneously encrypting multiple images of arbitrary size and type. Additionally, the proposed cross-plane scrambling scheme can effectively minimize pixel correlation. Finally, the security tests indicate that the encryption scheme possesses high security and can effectively withstand diverse attacks.

Keywords: Memristive Hindmarsh–Rose neuron; Two-parameter bifurcation; Medical image; Multi-image encryption; Cross-plane scrambling (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:189:y:2024:i:p1:s0960077924012530

DOI: 10.1016/j.chaos.2024.115701

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