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Novel hyperchaotic image encryption method using machine learning-RBF
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DOI：10.1007/s11071-024-09966-1.png)
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Abstract
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In this paper, we put forward a novel hyperchaotic image encryption method using machine learning-RBF. First, a new 4D continuous hyperchaotic system is designed to address the degradation issue of low-dimensional continuous chaotic systems, which has a simpler structure, wider chaotic range, better distribution, and higher complexity compared with other chaotic systems based on Hopfield-type neural networks. Additionally, it has good randomness and can be implemented using hardware-based digital signal processing. Then, based on this system, we explore a new image encryption method using machine learning-radial basis function (RBF) neural network and true random numbers. Results show that compared with some other algorithms, our method is more secure and withstand common attacks.
Keywords:
Chaotic systems
Radial basis function
Image encryption
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6
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1.4W
Citations:
4.1W
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