| 基于粗糙集数据挖掘和分类集成学习的网络入侵检测模型 |
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| 引用本文： | 王艳芳,张连华,白英彩.基于粗糙集数据挖掘和分类集成学习的网络入侵检测模型[J].计算机应用与软件,2006,23(4):120-122. |
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| 作者姓名： | 王艳芳 张连华 白英彩 |
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| 作者单位： | 1. 云南师范大学物理与电子信息学院,云南,昆明,650092
2. 上海交通大学计算机科学与工程系,上海,200030 |
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| 摘 要： | 基于多个特征或多个模型的集成（Ensemble）学习技术是智能网络入侵检测的重要研究方向，在现有研究基础上提出基于粗糙集分类、模型分发和攻击归类检测，并加以集成的学习式网络入侵检测模型，该模型不仅能提高网络入侵检测系统检测率，同时还结合了粗糙集能处理不确定信息、生成规则具有高解释性、特征排序在获得检测规则前完成等优点。
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| 关 键 词： | 网络入侵检测 粗糙集 数据挖掘 集成学习 |
| 收稿时间： | 09 14 2004 12:00AM |
| 修稿时间： | 2004-09-14 |
MODELING NETWORK INTRUSION DETECTION USING ROUGH SET DATA MINING AND ENSEMBLE LEARNING |
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| Wang Yanfang,Zhang Lianhua,Bai Yingcai.MODELING NETWORK INTRUSION DETECTION USING ROUGH SET DATA MINING AND ENSEMBLE LEARNING[J].Computer Applications and Software,2006,23(4):120-122. |
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| Authors: | Wang Yanfang Zhang Lianhua Bai Yingcai |
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| Affiliation: | 1.School of physics and Electrical Information Yunnan Normal University,Kunming Yunnan 650092, China; 2 . Department of Computer Science and Engineering, Shanghai Jiaotong University,Shanghai 200030, China |
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| Abstract: | Ensemble Learning technology is one of the important research directions in intelligent network intrusion detections.Based on the others' research in this domain,a new Network Intrusion Detection Modeling technology using Rough Set Data Mining,model distribution and Ensemble Learning is proposed,which can improve the detection rate and has the advantages of Rough Set Data Mining such as high model explanation,feature ranking and imprecise information adaption etc. |
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| Keywords: | Network intrusion detection Rough set Data mining Ensemble learning |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
