DocumentCode
511686
Title
A New Intrusion Prediction Method Based on Feature Extraction
Author
Cheng-Bin, Liao
Author_Institution
Sch. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
Volume
1
fYear
2009
fDate
28-30 Oct. 2009
Firstpage
7
Lastpage
10
Abstract
In order to find the attack in real time, an intrusion prediction method based on feature extraction algorithm was presented. Using CHI approach, the fields of network packet, which were irrelevant with attack type, were deleted, and the representative fields were selected to form feature database. Moreover, optimization extraction function was obtained by normalization method, and then network packets were effectively classified into normal or anomalous by the classifier. Experiment analysis proves that this intrusion prediction method have relatively low false positive rate and false negative rate, thus it effectively resolves the shortage of intrusion detection.
Keywords
feature extraction; security of data; support vector machines; CHI approach; SVM; false negative rate; false positive rate; feature database; feature extraction algorithm; intrusion prediction method; network packets; normalization method; optimization extraction function; Computer science; Discrete wavelet transforms; Feature extraction; Intrusion detection; Optimization methods; Packet switching; Prediction methods; Predictive models; Spatial databases; Switches; SVM; false negative rate; false positive rate; feature extraction; intrusion prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on
Conference_Location
Qingdao
Print_ISBN
978-0-7695-3881-5
Type
conf
DOI
10.1109/WCSE.2009.610
Filename
5403427
Link To Document