Correlation-base feature selector and AdaBoost applied in intrusion detection
Wei Ha · Information technology newsletter · 2014
Intrusion event recognition is the key to intrusion detection systems,and it also is a network data classification problems. For high recognition rate,through the selection algorithm based on relevant attributes,this paper selects a subset of the attributes with low redundant,identification intrusion by event AdaBoost algorithm. The experiments show that the correlation-based attribute selection algorithm and AdaBoost algorithm improve the classification accuracy and intrusion detection rate of events,reducing the false alarm rate of intrusion events.