Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems
The asymmetric optical cryptosystems have been widely concerned due to their prominent characteristics of high security and robustness against attacks. In this paper, a resolution adaptative network is proposed to attack the asymmetric optical cryptosystems, which solves the issue of requiring a lot...
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doaj-879109b09c0c4833b0f7555d56ce3b792021-03-30T03:46:42ZengIEEEIEEE Access2169-35362020-01-01818741918743010.1109/ACCESS.2020.30309869223733Resolution Adaptative Network for Cryptanalysis of Asymmetric CryptosystemsFan Wang0Jun Wang1https://orcid.org/0000-0003-1911-4676Renjie Ni2Zheng Zhu3Yuhen Hu4https://orcid.org/0000-0003-3427-0677School of Electronics and Information Engineering, Sichuan University, Chengdu, ChinaDepartment of Electrical and Computer Engineering, University of Wisconsin--Madison, Madison, WI, USASchool of Electronics and Information Engineering, Sichuan University, Chengdu, ChinaSchool of Electronics and Information Engineering, Sichuan University, Chengdu, ChinaSchool of Electronics and Information Engineering, Sichuan University, Chengdu, ChinaThe asymmetric optical cryptosystems have been widely concerned due to their prominent characteristics of high security and robustness against attacks. In this paper, a resolution adaptative network is proposed to attack the asymmetric optical cryptosystems, which solves the issue of requiring a lot of experiments to change the network structure and parameters for effectively attacking to ciphertexts with different resolutions. The proposed network of fixing the network structure and parameters can be trained by inputting plaintext-ciphertext pairs with different resolutions, and then the trained network model can generate the retrieved plaintexts with corresponding resolutions. Numerical simulation and analysis show that the classical asymmetric optical cryptosystems can be attacked by the proposed network successfully. Moreover, the excellent resolution adaptability of the proposed network is verified by training and testing the images with different resolutions. Furthermore, the generalization ability and robustness of the proposed network is verified. In general, the issue of the input resolution adaptability of the cryptanalysis network is addressed firstly to our best knowledge.https://ieeexplore.ieee.org/document/9223733/Resolution adaptative networkasymmetric cryptosystemscryptanalysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fan Wang Jun Wang Renjie Ni Zheng Zhu Yuhen Hu |
spellingShingle |
Fan Wang Jun Wang Renjie Ni Zheng Zhu Yuhen Hu Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems IEEE Access Resolution adaptative network asymmetric cryptosystems cryptanalysis |
author_facet |
Fan Wang Jun Wang Renjie Ni Zheng Zhu Yuhen Hu |
author_sort |
Fan Wang |
title |
Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems |
title_short |
Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems |
title_full |
Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems |
title_fullStr |
Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems |
title_full_unstemmed |
Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems |
title_sort |
resolution adaptative network for cryptanalysis of asymmetric cryptosystems |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
The asymmetric optical cryptosystems have been widely concerned due to their prominent characteristics of high security and robustness against attacks. In this paper, a resolution adaptative network is proposed to attack the asymmetric optical cryptosystems, which solves the issue of requiring a lot of experiments to change the network structure and parameters for effectively attacking to ciphertexts with different resolutions. The proposed network of fixing the network structure and parameters can be trained by inputting plaintext-ciphertext pairs with different resolutions, and then the trained network model can generate the retrieved plaintexts with corresponding resolutions. Numerical simulation and analysis show that the classical asymmetric optical cryptosystems can be attacked by the proposed network successfully. Moreover, the excellent resolution adaptability of the proposed network is verified by training and testing the images with different resolutions. Furthermore, the generalization ability and robustness of the proposed network is verified. In general, the issue of the input resolution adaptability of the cryptanalysis network is addressed firstly to our best knowledge. |
topic |
Resolution adaptative network asymmetric cryptosystems cryptanalysis |
url |
https://ieeexplore.ieee.org/document/9223733/ |
work_keys_str_mv |
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