%0 Journal Article %A ZHOU Mingwei %A LIU Yuan %T Anomaly classification based on fusion of NBC and PNN %D 2013 %R %J Computer Engineering and Applications %P 89-93 %V 49 %N 17 %X Classifying the network anomalies will help the administrators manage the network better. However, the single classifier has the problem that the results of the classification of the various of anomalies are not balanced, not comprehensive and other issues. In consideration of these facts, based on the research of the PNN algorithm and the NBC algorithm which are the most frequently used in classification filed, it proposes a new model using the fusion of the two algorithms. This model uses the accuracy of PNN and NBC that to classify the anomalies as weights, by calculating to obtain the?probability that belongs to each category of?the unknown flow, and the biggest probability will be choosed as the result. According to the verification of the KDD99 data set, experimental results show that the proposed model has the better classification rate and better balance than the simple classifier which through the PNN or NBC algorithm. %U http://cea.ceaj.org/EN/abstract/article_30882.shtml