An image encryption scheme by applying memristive Hindmarsh-Rose neuron model

Neurophysiological studies indicate that there are rich and complex dynamical characteristics in electrical actives between neurons. When neurons are stimulated by appropriate electromagnetic, the dynamical behavior for the nervous system can be changed, and electromagnetic has an important effect for the effectiveness of neurological diseases. To explore the complex dynamic effect of magnetic field in neuron activities, a new memristive HindMarsh-Rose neuron model can be developed by connecting a memristor into a simple 2 dimentional HindMarsh-Rose neuron model. It fond that the new neuron model has rich nonlinear dynamics and generate hidden attractors when changing electromagnetic induction. Neuron model as a nonlinear system, it has properties similar to a chaotic system system. So the memristive HindMarsh-Rose neuron model can be considered as a chaotic system to apply in image encryption algorithm. And an image encryption algorithm based on the memristive HindMarsh-Rose neuron model is proposed in this paper. The security analysis confirmed that enryption algorithm is well.

Automated summary

Neurophysiological studies have shown that there are complex dynamical characteristics in electrical activities between neurons. Electromagnetic stimulation can change the dynamics of the nervous system and affect the effectiveness of neurological diseases. By connecting a memristor to a 2-dimensional HindMarsh-Rose neuron model, a new memristive HindMarsh-Rose neuron model is developed to explore the complex dynamic effect of magnetic field on neuron activities. The model exhibits rich nonlinear dynamics and generates hidden attractors when the electromagnetic induction changes. This model can be considered as a chaotic system and applied in image encryption algorithm. A security analysis confirms the reliability of the proposed encryption algorithm.