A novel image encryption/decryption scheme based on chaotic neural networks

This paper presents a novel image encryption/decryption algorithm based on chaotic neural network (CNN). The employed CNN is comprised of two 3-neuron layers called chaotic neuron layer (CNL) and permutation neuron layer (PNL). The values of three RGB (Red, Green and Blue) color components of image constitute inputs of the CNN and three encoded streams are the network outputs. CNL is a chaotic layer where, three well-known chaotic systems i.e. Chua, Lorenz and Lü systems participate in generating weights and biases matrices of this layer corresponding to each pixel RGB features. Besides, a chaotic tent map is employed as the activation function of this layer, and makes the relationship between the plain image and cipher image nonlinear. The output of CNL, i.e. the diffused information, is the input of PNL, where three-dimensional permutation is applied to the diffused information. The overall process is repeated several times to make the encryption process more robust and complex. A 160-bit-long authentication code has been used to generate the initial conditions and the parameters of the CNL and PNL. Some security analysis are given to demonstrate that the key space of the new algorithm is large enough to make brute-force attacks infeasible and simulations have been carried out with detailed numerical analysis, demonstrating the high security of the new image encryption scheme.