Application Of Chaotic Neuron System In Image Encryption

Multimedia sharing and communication across public networks is becoming an important issue in our daily life.With increasing emphasis on security and privacy,how to protect multimedia data from eavesdropping and abuse has attracted worldwide attention.Encryption is the most direct way of protection.Traditional block ciphers have been reported to be unsuitable for multimedia data,so the characteristics of chaotic systems can be used to achieve satisfactory arrangement and diffusion performance for image encryption.Benefiting from Friedrich's pioneering contribution,in recent years,image encryption schemes based on chaos have begun to flourish.DNA computing originated from inherent advantages such as inherent parallelism,low power consumption and large amounts of storage,and it has also become a hot branch in cryptography.In this cryptographic system,DNA bases are used as information carriers,and their biological rules are used as arithmetic principles.They have common and mutually beneficial advantages in designing encryption algorithms.Therefore,encryption technology that combines DNA computing with chaos theory has become a natural choice.Combining the development status and existing problems of this research direction in recent years,this article studies the application of chaotic neuron system to image encryption,proposes an image encryption algorithm based on Hindmarsh-Rose(HR)neuron system,and verifies the security of this algorithm through experimental simulations Sex and effectiveness.The research content of the paper is mainly the following aspects:(1)This article summarizes and lists some common low-dimensional chaotic systems used in image encryption,and finds that these chaotic systems have been used by scholars in a combination of various encryption methods,and the system is too simple and the algorithm complexity is not high enough.Based on this,this article proposes an improved HR neuron model(referred to as HR neuron model in this article).(2)The dynamic behavior of HR neuron model is studied,and the system is applied to image encryption.First,perform nonlinear dynamic analysis on HR neuron,respectively calculate and draw the corresponding phase diagram,bifurcation diagram,Lyapunov exponent diagram,and perform dissipation and equilibrium point analysis to verify the chaotic dynamics of the system behavior.(3)The image encryption algorithm based on HR neuron proposed in this article.Firstly,the original image is preprocessed and a one-dimensional Logistic chaotic map is used to generate a chaotic sequence,which turns the chaotic sequence into a two-dimensional array with the same size as the original image.In order to achieve the effect of the correlation between plaintext and ciphertext,the initial value of the chaotic system will be determined by the original image,and the chaotic sequence generated by the chaotic system is used to select the DNA encoding and operation rules of each part.In the final scrambling,the three chaotic sequences generated by the HR chaotic system are used to perform the DNA operation rules of the row and column scrambling and selecting the original image respectively.The experimental results show that the encryption effect is good and the security is high.