A robust hybrid method for image encryption based on Hopfield neural network

In this paper, a robust hybrid image encryption algorithm with permutation-diffusion structure is proposed, based on chaotic control parameters and hyper-chaotic system. In the proposed method, a chaotic logistic map is employed to generate the control parameters for the permutation stage which results in shuffling the image rows and columns to disturb the high correlation among pixels. Next, in the diffusion stage, another chaotic logistic map with different initial conditions and parameters is employed to generate the initial conditions for a hyper-chaotic Hopfield neural network to generate a keystream for image homogenization of the shuffled image. The new hybrid method has been compared with several existing methods and shows comparable or superior robustness to blind decryption.

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