To reduce resource consumption, rise speed oftraining and testing, a new method oflDS based on division ofNN is proposed. The NN is divided into several small-scale neural networks according to the characteristic of the intrusion to perform learning and detecting this intrusion. In order to rise the speed of training and testing and to reduce the number of weights, every sub-neural network is divided into several smaller models. The detecting algorithm is developed and simulation is performed. The experimental results demonstrate that this method has the merit of fast learning and lower consum...
