A color image encryption algorithm based on Hopfield chaotic neural network

Abstract

In this paper, a new chaotic color image encryption algorithm is proposed. This algorithm uses a composite chaotic map combined with a staged Logistic map and Tent map for initial key processing and then obtains the parameters required for Arnold mapping through a function transformation needed to scramble the image. The diffusion phase uses Hopfield chaotic neural network to generate the self-diffusion chaotic matrix, and the key is generated by a function transformation; finally, the scrambled image is XORed with the key to obtain the final ciphertext image. Experimental results show that the proposed algorithm improves encryption efficiency, has good security performance, and can resist common attack methods.