Symmetric cryptosystem by neural network

被引：0
|
作者：
Dept. of Automat., Tsinghua Univ., Beijing 100084, China [1 ]
机构：
来源：
Qinghua Daxue Xuebao/Journal of Tsinghua University | 2001年 / 41卷 / 09期
关键词：
Block codes - Chaos theory - Control nonlinearities - Neural networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The non-linear and random characteristics of chaos provide an effective approach to enhance the information security. A perfect block cipher scheme with cipher block chaining (CBC) model is described for a symmetric encryption algorithm based on the chaotic attractors in discrete Hopfield neural networks. The method is simpler and more concise than DES, and some kinds of attacks can not easily unfold the scheme.
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页码：89 / 93
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