A fuzzy zeroing neural network and its application on dynamic Hill cipher

Cryptography is the core of information security, and the Hill cipher is one of the most important methods for cryptography. For the purpose of the improvement in the security of traditional Hill cipher (THC) with time-invariant key, a new dynamic Hill cipher (DHC) method with time-varying key is pr...

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Veröffentlicht in:	Neural computing & applications Jg. 37; H. 17; S. 10605 - 10619
Hauptverfasser:	Jin, Jie, Lei, Xiaoyang, Chen, Chaoyang, Lu, Ming, Wu, Lianghong, Li, Zhijing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.06.2025 Springer Nature B.V
Schlagworte:	Artificial Intelligence Color imagery Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Cryptography Data Mining and Knowledge Discovery Encryption Image Processing and Computer Vision Invariants Neural networks Probability and Statistics in Computer Science Robustness (mathematics) S.I.: Timely Advances of Deep Learning with applications and Data Driven Modeling Security Special Issue on Timely Advances of Deep Learning with applications and Data Driven Modeling Hill cipher Encryption and decryption Robustness Zeroing neural network (ZNN) Fuzzy theory
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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