Fractal-like models and Hilbert's synchronous scrambling diffusion encryption method

Abstract

This invention relates to the field of image encryption technology and addresses the problems of slow encryption speed and weak resistance to attacks in existing image encryption methods. The image encryption method described in this invention uses a ternary fractional discrete chaotic neural network system to generate a chaotic sequence related to the plaintext. A fractal sorting and scrambling process is then performed on the original image using a fractal model approach. To achieve better results, a double scrambling process is applied to both rows and columns. Finally, a synchronous scrambling and diffusion operation is performed according to the Hilbert curve traversal order, which can simultaneously change the position and size of pixel values. This method is the first to apply fractal thinking to the scrambling process in encryption, achieving good scrambling results. The synchronous scrambling and diffusion operation further improves the encryption efficiency to a certain extent.

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