Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic
Junfeng Tian, Yue Fu, Ying Xu, Jianling Wang · 2005
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.