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Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05)
Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic
Dalian, China
December 05-December 08
ISBN: 0-7695-2405-2
Jun-feng Tian, Hebei University, Baoding, China
Yue Fu, Hebei University, Baoding, China
Ying Xu, Hebei University, Baoding, China
Jian-ling Wang, Hebei University, Baoding, China
In order to improve detection performance of data mining-based intrusion detection system, this paper presents a method of combining multiple decision trees based on fuzzy logic, especially the fuzzy integral. The main idea of this method is to divide a great large dataset into several sub-datasets, mine on sub-datasets separately to construct different sub-decision trees, detect TCP data by different sub-decision trees, and then nonlinearly combine the results from multiple sub-decision trees by fuzzy integral. The experiment results show that this technique is superior to individual decision trees for intrusion detection in terms of classification accuracy.
Citation:
Jun-feng Tian, Yue Fu, Ying Xu, Jian-ling Wang, "Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic," pdcat, pp.256-258, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005
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