Network Intrusion Anomaly Detection Using Radial Basis Function Networks

The network intrusion detection is big threat to the current generation. In these days the usage of the Internet is part of our lives. The enormous growth of the computational intelligence makes us to use many devices, which are connected to the internet. This makes the attacker penetrates into the network to get the unauthorized access of the resources, to alter or modify them. By compromising the security mechanism and steal the valuable information. This makes the network intrusion detection needs to upgrade in every moment. The machine learning techniques enhances the detection rate by learning the new computational models. In this work we presented the Radial Basis Function (RBF) Networks are used to analyse the intrusion detection.