Image encryption algorithm based on hyperchaotic characteristics of cellular neural networks

Images have become the main media active in the information age. There is no doubt about the importance of image encryption technology. In order to solve the problem of image transmission security, the proposed algorithm is based on the hyper chaotic features of cellular neural network CNN combined with the general form of cubic function robust mapping and high-dimensional Lorenz system to adopt double diffusion-scrambling encryption operation on images. The simulation results show that the algorithm designed in this paper has excellent encryption effect. Its key space is large, ciphertext sensitivity is strong, information entropy value is 7.9994 close to ideal value, and it can effectively resist statistical attacks. The algorithm in this paper has high security and certain application value.