Title :
A New Intrusion Prediction Method Based on Feature Extraction
Author_Institution :
Sch. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
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;
Conference_Titel :
Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on
Conference_Location :
Qingdao
Print_ISBN :
978-0-7695-3881-5
DOI :
10.1109/WCSE.2009.610