The results indicate that the performance of ensembles of KFDA is better than that of FDA, PCA and pre-classifier. The prediction accuracy is about 86.5%.
In order to improve the detection rate and reduce the training time, KFDA-SVM intrusion detection technology is proposed which combines the feature extraction technology and classification algorithm.