a feature selection method based on entropy is proposed firstly. Five TCP connection features are selected for classifier. Then
a semi-supervised classification method that allows classifiers to be designed from training data consisting of only a few labelled and many unlabelled is proposed. The experiment shows that the detection results precedes on Kmeans method.