| TCP/IP Feature Reduction in Intrusion Detection |
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| 作者姓名： | LIU Yuling WANG Huiran TIAN Junfeng |
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| 作者单位： | College of Mathematics and Computer, Hebei University,Baoding 071002, Hebei, China |
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| 基金项目： | Foundation item： Supported by Natural Science Foundation of Hebei Province （F2004000133） |
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| 摘 要： | Due to the amount of data that an IDS needs to examine is very large, it is necessary to reduce the audit features and neglect the redundant features. Therefore, we investigated the performance to reduce TCP/IP features based on the decision tree rule-based statistical method（DTRS）. Its main idea is to create n decision trees in n data subsets, extract the rules, work out the relatively important features in accordance with the frequency of use of different features and demonstrate the performance of reduced features better than primary features by experimental resuits.
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| 关 键 词： | TCP/IP协议 网络安全 安全协议 计算机 |
| 文章编号： | 1007-1202（2007）01-0151-04 |
| 收稿时间： | 2006-05-20 |
TCP/IP feature reduction in intrusion detection |
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| LIU Yuling WANG Huiran TIAN Junfeng.TCP/IP Feature Reduction in Intrusion Detection[J].Wuhan University Journal of Natural Sciences,2007,12(1):151-154. |
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| Authors: | Liu Yuling Wang Huiran Tian Junfeng |
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| Institution: | (1) College of Mathematics and Computer, Hebei University, Baoding, 071002, Hebei, China |
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| Abstract: | Due to the amount of data that an IDS needs to exam- ine is very large, it is necessary to reduce the audit features and neglect the redundant features. Therefore, we investigated the performance to reduce TCP/IP features based on the decision tree rule-based statistical method(DTRS). Its main idea is to create n decision trees in n data subsets, extract the rules, work out the relatively important features in accordance with the frequency of use of different features and demonstrate the performance of re- duced features better than primary features by experimental re- sults. |
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| Keywords: | intrusion detection feature reduction decision tree data mining |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ |
