Title :
An Intrusion Detection Method Based on Outlier Ensemble Detection
Author :
Huang, Bin ; Li, Wen-fang ; Chen, De-li ; Shi, Liang
Author_Institution :
Electron. Inf. Eng. Dept., Putian Univ., Putian
Abstract :
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.
Keywords :
principal component analysis; security of data; KDD99 data set; PCA; anomaly detection approach; intrusion detection method; kernel density; outlier ensemble detection; outlier mining algorithm; principal components analysis; voting mechanism; Algorithm design and analysis; Clustering algorithms; Computer networks; Data analysis; Data mining; Information security; Intrusion detection; Kernel; Voting; Wireless communication; Ensemble; Intrusion Detection; Outlier Mining; Voting Mechanism;
Conference_Titel :
Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC '09. International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4244-4223-2
DOI :
10.1109/NSWCTC.2009.292
