Researches on Intrusion Detection System Based on RBF and Elman Hybrid Neural Network
Jun Zhang · Microelectronics & Computer · 2009
This paper proposes an intrusion detection model based on RBF and Elman Hybrid Neural Network model. This model has the memory function,can effective detection discrete and linked to attack. This model has the memory function,can effective detection discrete and linked to attack. The RBF network is a real-time mode classifier,and the Elman network can remember events. This system USES DARPA data set to test and evaluation. Use ROC curves to display of the test results. The experiment proves this system can effectively improve the detection rate,reduce false alarm rate and missed alarm rate.