DocumentCode :
2754240
Title :
Optimal Evaluation of Feature Selection in Intrusion Detection Modeling
Author :
Hu, Wei ; Li, Jianhua ; Shi, Jianjun
Author_Institution :
Dept. of Electron. Eng., ShangHai JiaoTong Univ.
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
5919
Lastpage :
5922
Abstract :
As a kind of data pre-process method, feature selection is an essential step in intrusion detection modeling. The method can improve the efficiency and accuracy of intrusion detection engine. Additionally, good features can provide excellent class separability. However, in the past researches on feature selection, the criteria and way about how to select the features in the raw data are seldom referred to. This paper shows us which type of features can aid us to achieve a better experimental result. In comparison to various types of intrusion attacks, the classical clustering algorithm, K-means is proposed to evaluate the features selected and prove the viewpoint based on KDD Cup 1999 DataSet. The knowledge of feature selection can be achieved by this means. With the usage of the statistics of network traffic, the better evaluation index, e.g. detection rate and false positive rate, are achieved than any other type of features. Finally, the paper provides the evaluation results of feature selection and we can regard them as knowledge for our future implementation
Keywords :
feature extraction; pattern clustering; security of data; unsupervised learning; K-means clustering algorithm; KDD Cup 1999 DataSet; anomaly detection; data preprocess method; feature selection; intrusion attacks; intrusion detection modeling; network traffic statistics; unsupervised learning; Clustering algorithms; Data engineering; Data mining; Engines; Intrusion detection; Partitioning algorithms; Statistics; Telecommunication traffic; Traffic control; Unsupervised learning; Anomaly Detection; Clustering Algorithm; Feature Selection; Unsupervised Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1714214
Filename :
1714214
Link To Document :
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