Abstract
Security has become an important issue for networks. Intrusion detection technology is an effective approach in dealing with the problems of network security. In this paper, we present an intrusion detection model based on PCA and MLP. The key idea is to take advantage of different feature of NSL-KDD data set and choose the best feature of data, and using neural network for classification of intrusion detection. The new model has ability to recognize an attack from normal connections. Training and testing data were obtained from the complete NSL-KDD intrusion detection evaluation data set.
