论文信息 - An Intrusion Detection Method Based on Outlier Ensemble Detection

An Intrusion Detection Method Based on Outlier Ensemble Detection

In this paper, we try to bring the concept of Ensemble into Outlier Detection. Two Outlier mining algorithms are ensembled: one based on similar coefficient sum and the other based on Kernel Density. An anomaly detection approach based on Voting Mechanism is proposed and applied into Intrusion Detection. We convert the character feature into numerical value by code mapping and use Principal Components Analysis(PCA) to reduce dimension. We apply this technique on KDD99 data set and get satisfactory results.

[1] Ana L. N. Fred,et al. Finding Consistent Clusters in Data Partitions , 2001, Multiple Classifier Systems.

[2] Shigeo Abe DrEng. Pattern Classification , 2001, Springer London.

[3] Joydeep Ghosh,et al. Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions , 2002, J. Mach. Learn. Res..

[4] Leonid Portnoy,et al. Intrusion detection with unlabeled data using clustering , 2000 .

[5] David G. Stork,et al. Pattern Classification , 1973 .

[6] Andrew H. Sung,et al. Intrusion detection using neural networks and support vector machines , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[7] Guadalupe I. Janoski,et al. Intrusion Detection : Support Vector Machines and Neural Networks , 2002 .

[8] Huang Bin. An Intrusion Detection Method Based on Outlier Detection , 2009 .

[9] Li Kun-lun. AN INTRUSION DETECTION METHOD BASED ON SVM , 2003 .