Acta Scientific Computer Sciences

Review Article Volume 5 Issue 1

A Review of Artificial Neural Network Based Block Cipher in China

Wanni Huang*

Department of Information Engineering, Guilin Institute of Information Technology, China

*Corresponding Author: Wanni Huang, Department of Information Engineering, Guilin Institute of Information Technology, China.

Received: August 23, 2022; Published: December 13, 2022


In the era of swift changes in technical information, the development of any technology should not be limited to the technology itself. In the age of rapid development of artificial intelligence technology, cryptography research should not be limited to traditional research based only on number theory. The combination of artificial neural networks and block cipher has essential value and significance for promoting the development of cryptography. The article takes the concept of chaos as the connection and entry point of cryptography and artificial neural network research and further elaborates on the research process of combining cryptography and artificial neural network. In addition, the article further discusses and summarizes the critical directions of the early research on chaotic block ciphers for academic circles in China. Finally, this paper analyzes and summarizes the new progress of neural networks and block cipher research in China. This paper aims to discuss the antecedents and current status of the research on neural network block ciphers and provide a reference for future research on neural network block ciphers.

Keywords: Chaos; Artificial neural network; Block cipher; Symmetric cipher; Encryption


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Citation: Wanni Huang.,et al. “A Review of Artificial Neural Network Based Block Cipher in China".Acta Scientific Computer Sciences 5.1 (2023): 73-78.


Copyright: © 2023 Wanni Huang.,et al 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.


Acceptance rate35%
Acceptance to publication20-30 days

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