Intrusion Prevention Systems (IPS) are deployed in-line with the network segment being protected. All data that flows between the protected segment and the rest of the network must pass through the NIPS. As the traffic passes through the IPS, it is inspected for the presence of an attack. Like viruses, most intruder activities have some sort of signatures. A growing number of Sensor and Ad-hoc networking protocols and location-aware services require that mobile nodes learn the position of their neighbors for improving the securities in any network environment. However, such a process can be easily abused or disrupted by adversarial nodes. In absence of a-priority trusted nodes, the discovery and verification of neighbor positions presents challenges that have been scarcely investigated in the literature. Trust Management Approaches and clustering based approaches are used to reduce the false rejection ratio in mobile nodes and agents. First identify the trusted nodes in networks, then packets will send through that trusted nodes. Trusted nodes are identified based on trust values for identify the neighboring nodes for verification process for improving the Packet Delivery Ratio and Energy Consumption.
