Intrusion Detection Using Neural Based Hybrid Classification Methods
Data mining is the use of algorithms to extract the information and patterns derived by the knowledge discovery in databases process. Classification is a very common data mining task. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. Due to increasing incidents of cyber attacks, building effective intrusion detection systems are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. This paper presents two classification methods involving multilayer perceptron and radial basis function and an ensemble of multilayer perceptron and radial basis function.