A novel intrusion detection system based on KPCA and RVM with PSO model

The aim of the present work was to design and develop of a Data mining based Network Intrusion Detection System which can detect intrusions based on misuse detection technique and learning algorithm. The work also aimed at reducing number of false alarms by characterizing the target network with appropriate network parameters and analyzing them with mathematical models. This project proposed the KPCA and RVM with PSO for intrusion detection system. The Relevance Vector Machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and probabilistic classification. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification.