Journal
OPTIK
Volume 268, Issue -, Pages -Publisher
ELSEVIER GMBH
DOI: 10.1016/j.ijleo.2022.169758
Keywords
Image encryption; Chaotic neural network; Network with multistable hyperchaos; Security analysis; Synchronization accuracy
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Funding
- National Natural Science Foundation of China [11972274, 12172267]
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This paper proposes an image encryption scheme using complex and time-delayed neural networks, which greatly enhances the security and resistance against attacks.
In this paper a new image encryption scheme is proposed, by which the pixel values are bit-level shuffled by the encryption sequences generated by a complex network, while the pixel positions of diffused images are scrambled by the chaotic sequences generated by a time-delayed neural network. In this way the key space is greatly enlarged through the simultaneous use of the time -delayed neural network and the complex network with a high dimensional multistable hyper -chaotic system as nodal model. In particular, different nodes in the complex network are selected to generate the encryption and the decryption sequences. To achieve the synchronization accu-racy necessarily for correct decryption, the number of nodes needed in the fully connected complex network is investigated and determined. Through applications on different kinds of plain images, the proposed algorithm exhibits excellent performance on security, i.e., with better sta-tistical and differential characteristics, better plain-image key sensitivity and a large enough key space. In addition the encryption scheme can also resist various knowing attacks.
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