Cryptosystem for Grid Data Based on Quantum Convolutional Neural Networks and Quantum Chaotic Map

被引:0
|
作者
Ru-Chao Tan
Xing Liu
Ru-Gao Tan
Jian Li
Hui Xiao
Jian-Jun Xu
Ji-Hai Yang
Yang Zhou
De-Lin Fu
Fang Yin
Lang-Xin Huang
Li-Hua Gong
机构
[1] Information & Telecommunication Branch of State Grid Jiangxi Electric Power Co.,Department of Electronic Information Engineering
[2] Ltd.,undefined
[3] Nanchang University,undefined
关键词
Cryptosystem; Quantum convolutional neural network; Quantum chaotic map;
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学科分类号
摘要
Motivated by the existing circuit model of quantum convolutional neural network, a new quantum convolutional neural network circuit model is devised, which is combined with quantum chaotic map to construct a symmetric cryptosystem. Quantum chaotic map produces key stream for encryption and decryption. The cryptosystem simulates the basic process of communication. Theoretical analysis manifests that the cryptosystem is effective. Additionally, simulation experiments based on MNIST data set show that the cryptosystem is secure. Furthermore, the proposed cryptosystem can be applied not only for image data, but for text data. Therefore, the grid data can be encrypted by utilizing the cryptosystem.
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页码:1090 / 1102
页数:12
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