| 运用核Fisher鉴别分析和MPM分类器的入侵检测 |
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| 引用本文： | 陈振国,李冬艳.运用核Fisher鉴别分析和MPM分类器的入侵检测[J].电子科技大学学报(社会科学版),2007(6). |
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| 作者姓名： | 陈振国 李冬艳 |
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| 作者单位： | 华北科技学院计算机系 河北三河065201 |
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| 摘 要： | 为了提高分类器的正确率和减少训练时间,将特征提取技术与分类算法结合,提出了一种基于核Fisher鉴别分析和最小极大概率机算法的入侵检测算法。利用核Fisher鉴别分析技术提取关键特征,运用最小极大概率机对提取特征后的数据进行分类,采用离线数据集KDDCUP99进行实验。实验结果表明,该算法是可行和有效的,使分类性能和训练时间都得到了提高。
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| 关 键 词： | 数据分类 入侵检测 核Fisher鉴别分析 最小极大概率机 网络安全 |
Intrusion Detection Based on Kernel Fisher Discriminant Analysis and Minimax Probability Machine Classifier |
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| CHEN Zhen-guo,LI Dong-yan.Intrusion Detection Based on Kernel Fisher Discriminant Analysis and Minimax Probability Machine Classifier[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),2007(6). |
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| Authors: | CHEN Zhen-guo LI Dong-yan |
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| Abstract: | To improve the performance of Minimax Probability Machine (MPM) in the detection rate and the training time, Intrusion Detection Based on Kernel Fisher Discriminant Analysis and Minimax Probability Machine Classifier (KFDA-MPM) algorithm is proposed which combines the feature extraction technology and classification algorithm. In this method, the KFDA is used to extract the optimal feature set and then the MPM is adopted to classify the optimization data. Results of the experiment using the Knowledge Discovery and Data Mining Cup 1999 (KDDCUP99) datasets indicate the effectiveness of the algorithm. |
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| Keywords: | data classification intrusion detection kernel Fisher discriminant analysis minimax probability machines network security |
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