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Content Provider | IEEE Xplore Digital Library |
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Author | Guan Xiaoqing Guo Hebin Chen Luyi |
Copyright Year | 2010 |
Description | Author affiliation: Northern Beijing Vocational Education Institute Beijing 101400, P.R. China (Guo Hebin) || Beijing Vocational College of Electronic Science Beijing 100026, P.R. China (Guan Xiaoqing; Chen Luyi) |
Abstract | It is necessary to study a kind of network intrusion detection method which realizes faster attack detection and response. In order to improve the network intrusion detection precision further, Network intrusion detection method based on Agent and SVM is proposed to recognize the intrusion types in the paper. The network intrusion detection system based Agent and SVM are created. Then, network Intrusion detection model based on SVM is gained, and the process of intrusion detection by SVM is given. The experimental results demonstrate that the presented method in this paper is better than artificial neural network. |
Starting Page | 399 |
Ending Page | 402 |
File Size | 459671 |
Page Count | 4 |
File Format | |
ISBN | 9781424452637 |
DOI | 10.1109/ICIME.2010.5477694 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-04-16 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Agent Artificial neural networks Educational institutions intrusion detection Data mining Lagrangian functions network Support vector machines Learning systems support vector machine Intrusion detection Support vector machine classification IP networks Kernel |
Content Type | Text |
Resource Type | Article |
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