TY - JFULL AU - Jianhua Wang and Yan Yu PY - 2013/5/ TI - Research on Hybrid Neural Network in Intrusion Detection System T2 - International Journal of Computer and Information Engineering SP - 480 EP - 485 VL - 7 SN - 1307-6892 UR - https://publications.waset.org/pdf/7003 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 76, 2013 N2 - This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid model intrusion detection system uses DARPA data set to do test evaluation. It uses ROC curve to display the test result intuitively. After the experiment it proves this hybrid model intrusion detection system can effectively improve the detection rate, and reduce the rate of false alarm and fail. ER -