| 基于组合分类器的校园网入侵检测 |
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| 引用本文： | 周宓.基于组合分类器的校园网入侵检测[J].新乡学院学报(自然科学版),2012(5):421-422,425. |
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| 作者姓名： | 周宓 |
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| 作者单位： | 泉州师范学院应用科技学院 |
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| 摘 要： | 为了增强校园网络的安全性，提出 KPCA 和 BP 神经网络相结合的组合分类器法构造入侵检测系统.先用 KPCA 对原始数据进行降维处理，而后用 BP 神经网络对新的数据进行分类检测. 结果表明，该方法能有效地缩短检测时间，提高检测效率.
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| 关 键 词： | KPCA BP 神经网络 入侵检测 检测时间 |
Intrusion Detection of Campus Network Based on Combined Classifier |
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| Authors: | ZHOU Mi |
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| Institution: | ZHOU Mi(College of Applied Science and Technology,Quanzhou Normal University,Quanzhou 362000,China) |
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| Abstract: | To improve safety of campus network,an intrusion detection system is proposed by combined classifier which is combination of KPCA technology and BP Neural Network.First,KPCA technology is used to decrease the dimensions of raw data,and then the new data samples are classified by BP neural network.Results show that the method can shorten detection time and enhance detection rate. |
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| Keywords: | KPCA BP neural network intrusion detection detection time |
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