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Cryptosystem for Grid Data Based on Quantum Convolutional Neural Networks and Quantum Chaotic Map
- Source :
- International Journal of Theoretical Physics. 60:1090-1102
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- 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.
- Subjects :
- Physics and Astronomy (miscellaneous)
010308 nuclear & particles physics
Computer science
business.industry
General Mathematics
Data_CODINGANDINFORMATIONTHEORY
Encryption
Grid
01 natural sciences
Convolutional neural network
Image (mathematics)
ComputerSystemsOrganization_MISCELLANEOUS
0103 physical sciences
Key (cryptography)
Cryptosystem
Hardware_ARITHMETICANDLOGICSTRUCTURES
010306 general physics
business
Algorithm
Quantum
MNIST database
Computer Science::Cryptography and Security
Subjects
Details
- ISSN :
- 15729575 and 00207748
- Volume :
- 60
- Database :
- OpenAIRE
- Journal :
- International Journal of Theoretical Physics
- Accession number :
- edsair.doi...........87020d57e1b074358e209944867e310e
- Full Text :
- https://doi.org/10.1007/s10773-021-04733-z