Intrusion detection system based on improved BP Neural Network and Decision Tree

According to the attributes of both BP Neural Network and Decision Tree, this paper presents an advanced complex-algorithm model in order to improve the ability of intrusion detection. The simulating results show that the new system not only can increase the average detection rate and reduce the failing, but it can also be more effective to simplify the complexity, raise the detection speed and promote the accuracy by use of abstracting rules and paralleled dealing method in matching process.