Adaptive Security Model in Real-time Intrusion Detection Environment

被引：0
|
作者：
Han, Myung-Mook [2 ]
Li, Dong-Hui [2 ]
Jeong, Taikyeong Ted [1 ]
机构：
[1] Myongji Univ, Dept Elect Engn, Yongin, South Korea
[2] Kyungwon Univ, Dept Comp Engn, Songnam, South Korea
来源：
INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | 2011年 / 14卷 / 04期
关键词：
Neural network; Preprocessor; Intrusion detection; Sage; Feature selection; ALGORITHMS;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In the paper, we will introduce a new system to deal with the interne security which has become a crucial issue with the rapidly development of computer technology. The hard core includes two parts: preprocessor and neural network. We will use a preprocessor which uses a fire-new feature selection algorithm named GBS (PGBS) and a widely used neural network named back propagation neural network (BP network) to construct the system. The system can automatically and rapidly adapt the change when there is a new intrusion appearing in the network. The result of experiments show the system is greater utility and higher correct rate.
引用
收藏
页码：1373 / 1383
页数：11
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