| 网络入侵检测系统中的数据缩减技术 |
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| 引用本文： | 邹 涛,孙宏伟,田新广,张尔扬. 网络入侵检测系统中的数据缩减技术[J]. 国防科技大学学报, 2003, 25(6): 16-20 |
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| 作者姓名： | 邹 涛 孙宏伟 田新广 张尔扬 |
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| 作者单位： | 国防科技大学电子科学与工程学院,湖南,长沙,410073 |
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| 摘 要： | 在进行事件分析之前,网络入侵检测系统首先要面对数据缩减的问题。以ANIDS为背景,分析了两种重要的数据缩减技术:相关特征子集选择和特征再构造。提出了一种基于Wrapper方法的最优特征子集选取算法SRRW。在考虑学习算法偏置的情况下,通过识别强相关特征并引入约束,能够更快地搜索并获得最优的相关特征子集。从特征再构造角度出发实现数据缩减,并通过因子负荷量矩阵分析了原始特征之间的相关性。
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| 关 键 词： | 网络入侵检测 数据缩减 相关特征选取 主成分分析 |
| 文章编号： | 1001-2486(2003)06-0016-05 |
| 收稿时间： | 2003-05-13 |
| 修稿时间： | 2003-05-13 |
Data Reduction in Network Based on the Intrusion Detection System |
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| ZOU Tao,SUN Hongwei,TIAN Xinguang and ZHANG Eryang. Data Reduction in Network Based on the Intrusion Detection System[J]. Journal of National University of Defense Technology, 2003, 25(6): 16-20 |
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| Authors: | ZOU Tao SUN Hongwei TIAN Xinguang ZHANG Eryang |
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| Affiliation: | College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China |
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| Abstract: | NIDSs deal with the problem of data reduction before analyzing the events. Two important measures used in ANIDS are proposed: FSS and new feature construction. A novel algorithm named SRRW is put forward first, which can produce OFS by recognizing all strongly relevant features and restrict them in searching process. A feature construction method is used to get the OFS. The correlations between the original features can be analyzed by factor loading matrix. |
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| Keywords: | NIDS data reduction relevant feature selection PCA |
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