Application Of ANN In IDS

This article was completed based on the IDS algorithm design of TYKJ CO. , LTD. It mainly investigated the computer programming realization of the nonlinear mathematic model and the algorithm of the Artifical Neural Network, and thus provided technical support to the nonlinear conformity disposal of the complex IDS information.There are lots of nonlinear problems in IDS working. The integrated analyzing and sorting toward IDS data, the accurate forecasting of the intruders and common visitors etc, all come down to the multiple data conformity disposal. Therefore, it is vitally important to develop a perfect nonlinear conformity disposal method. However, some favorable characters of ANN can content these IDS working demands perfectly,in additon,the capability of nonlinear mapping of ANN also make sure that the system can execute simple or complex classification and save the information into the coefficent of connecting power,maintain the network robust and fault toleration .so more and more people alter one after another their working focus to the nonlinear mathematic model based on the ANN in order to resolve the complex problems in IDS system much better.This kind of investigations have acquired some accomplishments at present, but much of these accomplishments were limited to resolve certain frondose application using certain fixed network model and were far from satisfying the minimizing forecasting faults demands of IDS improving. The purpose of this theme is to establish a multi-net-model and make it generally applicable during the arithmetic realization process to content all application demands and thus minimize forecasting faultsIn the end of this article applying the advanced BP network to the ES in IDS minimized the false forecasting, Further more it discussed the process of using Visual C++ to realize these networks.