A Heuristic Profile Based Intruder Detection Scheme on MANET

The major challenge in the design of MANETs is their vulnerability to security attacks. The rapid proliferation of multiple heterogeneous mobile / wireless networks and mobile computing applications attribute for the change in security architecture. The major obstacle for the detection of an internal intrusion is that the nodes are under consistent mobility. Nodes move constantly within the internal domain of MANET. In such cases, the traditional intrusion detection approach has to be allocated to several strategic points to identify an intrusion or attempted attack at the moment it occurs. A number of algorithms and schemes for detecting intruders in MANET exist, but all systems suffer from performance penalties and high false alarm rates. This research work concentrates on the development of an architectural model for identifying intruders using profile based anomaly or misuse detection mining approach. The proposed architecture aims to minimize the costs involved in monolithic intrusion detection and works on identifying intruders based on XML / ontology setup in mobile nodes. The model is simulated using ns2 simulator.