A fractional-order CNN hyperchaotic system for image encryption algorithm. (4th January 2021) - Wang, Yanzhang; Yang, Feifei
Abstract: This paper proposes a fractional-order cellular neural network (CNN) chaotic system for image encryption algorithm to explore the application of fractional-order CNN hyperchaotic system in chaotic secure communication. Firstly, a fractional-order CNN hyperchaotic system is defined based on CNN hyperchaotic system. The numerical solutions of the fractional-order CNN hyperchaotic system are calculated by Adomian decomposition algorithm. The dynamic characteristics of the of the fractional-order CNN hyperchaotic system are analyzed. Then to verify the image encryption application of the fractional-order CNN hyperchaotic system, we designed an image encryption scheme through fractional-order CNN hyperchaotic sequence, the principle of symmetry of main diagonal of matrix and XOR operation. Finally, the results illustrate that the fractional-order CNN hyperchaotic sequence has good randomness, which show that the fractional-order CNN hyperchaotic system more suitable for chaotic secure communication applications. The security performances of the algorithm show that the designed algorithm can effectively encrypt and decrypt image, and has better security performance.