Abstract
This paper proposes a new chaotic image encryption algorithm. Firstly, an original phased composite chaotic map is used. The comparative study shows that the map cryptographic characteristics are better than the Logistic map, and the map is used as the controller of Fisher-Yates scrambling. Secondly, with the higher complexity of the fractional-order five-dimensional cellular neural network system, it is used as a diffusion controller in the encryption process. And mix the secret key, mapping and plaintext, we can obtain the final ciphertext. Finally, the comparative experiments prove that the proposed algorithm improves the encryption efficiency, has good security performance, and can resist common attack methods.
Highlights
Introduction to chaotic systems2.1 Fractional 5-dimensional cellular neural network modelThe cellular neural network was proposed by Chua and Yang in a combination of cellular automata and Hopfield neural networks
Some color image encryption algorithms based on chaos theory have been proposed [12,13,14,15], while highdimensional chaotic systems, especially hyperchaotic systems, have large key spaces, complex and unpredictable nonlinear behavior, using hyperchaotic systems to encrypt data will improve the security of the cryptosystem
The chaotic sequences generated by CNN are used for encryption, but due to the defects of its own algorithm, its encryption effect cannot meet the resistance of existing attack methods
Summary
With the rapid development of the computer industry, more and more multimedia information needs to ensure its encryption status during transmission to prevent others from gaining privacy and conduct improper behavior. Some color image encryption algorithms based on chaos theory have been proposed [12,13,14,15], while highdimensional chaotic systems, especially hyperchaotic systems, have large key spaces, complex and unpredictable nonlinear behavior, using hyperchaotic systems to encrypt data will improve the security of the cryptosystem. The encryption scheme with large key space can be designed; CNN dynamic equation can directly generate a better random matrix, which can design a digital image encryption scheme more conveniently. This paper proposes a color image encryption algorithm based on cellular neural network. This paper will use the use of fractional-order 5D neural network to make it better applied to the field of image encryption against existing attacks.
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