Novel image encryption algorithm based TLM hyperchaotic cellular neural network

Since chaos is sensitive for initial values, it is very suitable for data encryption. An image encryption algorithm based on hyper-chaotic control parameters and mixed scrambling diffusion structure of higher -order chaotic system was presented. The encryption algorithm included scrambling step and diffusion step. In the scrambling step, the composite chaotic map was used to generate the alignment phase control parameters and scramble for the high-level image cross -correlation between the adjacent pixels. In the diffusion step, the composite chaotic map with the different initial states and parameters was used to generate the initial conditions for hyper-chaotic cellular neural networks in order to generate the key stream. This method was evaluated by known plaintext attack and chosen plaintext attack, key space, image histogram, and simulations show good results. Compared with several other related algorithms, it has better anti -aggressive and key sensitivity is high. It can be applied to the image encryption.