| Learning Vector Quantization Neural Network Method for Network Intrusion Detection |
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| 作者姓名： | YANG Degang CHEN Guo WANG Hui LIAO Xiaofeng |
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| 作者单位： | [1]Department of Computer Science and Engineering, Chongqing University, Chongqing 400044, China [2]Department of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047, China [3]Department of Modem Educational Technology, Chongqing Normal University, Chongqing 400047, China [4]Department of Mathematics, Leshan Normal College, Leshan 610043, Sichuan, China |
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| 基金项目： | Foundation item： Supported by the National Natural Science Foundation of China （60573047）, Natural Science Foundation of the Science and Technology Committee of Chongqing （8503） and the Applying Basic Research of the Education Committee of Chongqing （KJ060804） |
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| 摘 要： | A new intrusion detection method based on learning vector quantization （LVQ） with low overhead and high efficiency is presented. The computer vision system employs LVQ neural networks as classifier to recognize intrusion. The recognition process includes three stages： （1） feature selection and data normalization processing;（2） learning the training data selected from the feature data set; （3） identifying the intrusion and generating the result report of machine condition classification. Experimental results show that the proposed method is promising in terms of detection accuracy, computational expense and implementation for intrusion detection.
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| 关 键 词： | 向量 量化方法 神经网络 网络侵扰检测 网络安全 计算机 |
| 文章编号： | 1007-1202（2007）01-0147-04 |
| 收稿时间： | 2006-04-20 |
Learning vector quantization neural network method for network intrusion detection |
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| YANG Degang CHEN Guo WANG Hui LIAO Xiaofeng.Learning Vector Quantization Neural Network Method for Network Intrusion Detection[J].Wuhan University Journal of Natural Sciences,2007,12(1):147-150. |
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| Authors: | Yang Degang Chen Guo Wang Hui Liao Xiaofeng |
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| Institution: | (1) Department of Computer Science and Engineering, Chongqing University, Chongqing, 400044, China;(2) Department of Mathematics and Computer Science, Chongqing Normal University, Chongqing, 400047, China;(3) Department of Modern Educational Technology, Chongqing Normal University, Chongqing, 400047, China;(4) Department of Mathematics, Leshan Normal College, Leshan, 610043, Sichuan, China |
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| Abstract: | A new intrusion detection method based on learning vector quantization (LVQ) with low overhead and high efficiency is presented.
The computer vision system employs LVQ neural networks as classifier to recognize intrusion. The recognition process includes
three stages: 1 feature selection and data normalization processing; 2 learning the training data selected from the feature
data set; 3 identifying the intrusion and generating the result report of machine condition classification. Experimental results
show that the proposed method is promising in terms of detection accuracy, computational expense and implementation for intrusion
detection.
Biography: YANG Degang (1976–), male, Ph.D. candidate, Associate professor of Chongqing Normal University, research direction: information
security. |
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| Keywords: | intrusion detection learning vector quantization neural network feature extraction |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ |
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