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Digital images, because of their large data volume and high data correlation, combined with information image and vividness, have become one of the important means for people to express information. 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.
#Neural network the unscrambler password
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript.įunding: This research is supported by the National Natural Science Foundation of China (No: 61672124), the Password Theory Project of the 13th FiveYear Plan National Cryptography Development Fund (No: MMJJ20170203), Liaoning Province Science and Technology Innovation Leading Talents Program Project (No: XLYC1802013), Key R&D Projects of Liaoning Province (No: 2019020105-JH2/103), and Jinan City ‘20 universities’ Funding Projects Introducing Innovation Team Program (No: 2019GXRC031) to XW.Ĭompeting interests: The authors have declared that no competing interests exist.
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Received: ApAccepted: JPublished: July 15, 2020Ĭopyright: © 2020 Wang et al.
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PLoS ONE 15(7):Įditor: Jun Ma, Lanzhou University of Technology, CHINA Citation: Wang X, Su Y, Luo C, Wang C (2020) A novel image encryption algorithm based on fractional order 5D cellular neural network and Fisher-Yates scrambling.