A Color Image Encryption Algorithm Based on Double Fractional Order Chaotic Neural Network and Convolution Operation

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Abstract

A color image encryption algorithm based on double fractional order chaotic neural network (CNN), interlaced dynamic deoxyribonucleic acid (DNA) encoding and decoding, zigzag confusion, bidirectional bit-level diffusion and convolution operation is proposed. Firstly, two fractional order chaotic neural networks (CNNs) are proposed to explore the application of fractional order CNN in image encryption. Meanwhile, spectral entropy (SE) algorithm shows that the sequence generated by the proposed fractional order CNNs has better randomness. Secondly, a DNA encoding and decoding encryption scheme with evolutionary characteristics is adopted. In addition, convolution operation is utilized to improve the key sensitivity. Finally, simulation results and security analysis illustrate that the proposed algorithm has high security performance and can withstand classical cryptanalysis attacks.

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Li, N., Xie, S., & Zhang, J. (2022). A Color Image Encryption Algorithm Based on Double Fractional Order Chaotic Neural Network and Convolution Operation. Entropy, 24(7). https://doi.org/10.3390/e24070933

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