Fortification of Hybrid Intrusion Detection System Using Variants of Neural Networks and Support Vector Machines
Intrusion Detection Systems (IDS) form a key part of system defence, where it identifies abnormal activities happening in a computer system. In recent years, different soft computing based techniques have been proposed for the development of IDS. On the other hand, intrusion detection is not yet a perfect technology. This has provided an opportunity for data mining to make quite a lot of important contributions in the field of intrusion detection. In this paper, the authors have proposed a new hybrid technique by utilizing data mining techniques such as fuzzy C means clustering, Fuzzy neural network /Neurofuzzy and Radial Basis Function(RBF) SVM for fortification of the Intrusion Detection System.