Hybrid Feature Selection for Modelling Intrusion Detection System and Cyber Attack Detection System
Intrusion Detection Systems (IDS) and Cyber Attack Detection System (CADS) have to be provided in a generalized discriminant analysis algorithm. It is an important approach to nonlinear features and extensively used tool for ensuring network security. Complex relationships exist between the features, which are difficult for humans to discover. The conventional linear discriminant analysis feature reduction technique is not suitable for nonlinear data set. Artificial neural network and C4.5 classifiers to result in supervisory algorithm are used. If real-time detection is desired IDS must reduce the amount of data to be processed.