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基于元胞自动机的S盒的性质与神经网络实现研究
引用本文:黄俊君,关杰.基于元胞自动机的S盒的性质与神经网络实现研究[J].电子学报,2000,48(12):2462-2468.
作者姓名:黄俊君  关杰
作者单位:解放军战略支援部队信息工程大学, 河南郑州 450001
摘    要:基于元胞自动机(CA)的S盒密码学性质良好且软硬件实现代价低,被用于Keccak、SIMON等密码算法.本文研究了基于CA的S盒的性质,给出并证明了此类S盒的三个重要性质:移位不变性、镜面对称性和互补性;同时研究了基于CA的S盒的神经网络实现方法,指出相比一般的S盒,基于CA的S盒在进行神经网络实现时可以用更简单的结构、消耗更少的资源来完成,并且给出了一种权重阈值搜索算法可以方便快速地实现基于CA的S盒的神经网络结构.

关 键 词:元胞自动机  S盒  Keccak  神经网络  权重阈值  搜索算法  
收稿时间:2019-10-11

Research on Properties and Neural Networks Implementation of Cellular Automata Based S-Boxes
HUANG Jun-jun,GUAN Jie.Research on Properties and Neural Networks Implementation of Cellular Automata Based S-Boxes[J].Acta Electronica Sinica,2000,48(12):2462-2468.
Authors:HUANG Jun-jun  GUAN Jie
Affiliation:PLA SSF Information Engineering University, Zhengzhou, Henan 450001, China
Abstract:Cellular automata(CA) based S-boxes are the type of S-boxes with good cryptography and low cost of hardware as well as software implementation,which are used in Keccak,SIMON,and other cryptographic algorithms.This paper studied the properties of CA-based S-boxes,and the three important properties were given and proved,including shift invariance,mirror symmetry and complementarity.Meanwhile,the neural network implementation for CA-based S-boxes was studied,which demonstrated that the CA-based S-boxes could be implemented with simpler structure and less resources than the general one.In addition,a weight threshold search algorithm which could easily and quickly implement the neural network structure of CA-based S-boxes was shown.
Keywords:cellular automata  S-boxes  Keccak  neural networks  weight and threshold  search algorithm  
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