Enhancing the Security for Manet by Identifying Untrusted Nodes using Uncertainity Rules

Background/Objectives: Trust based models offer security against vulnerabilities due to the dynamic and open wireless medium. The raise up of uncertain reasoning methods originates from the artificial intelligence leads to trust management protocols for the creation of secure environment in MANET. Methods/Statistical Analysis: In this paper, two schemes namely, direct and indirect observation based trust evaluation are proposed. Initially, the network is formed to investigate the security. The utilization of full probability model in Bayesian interface evaluates the trust from the observer node in direct observation scheme. Alternatively, the neighbor hop information is used in the derivation of trust value in indirect observation scheme. Another type of uncertain reasoning called Dempster-Shafter theory calculates the trust value after the observation schemes. Finally, the Dijkstra's algorithm establishes the routing process on the basis of shortest path. Findings: The proposed observation schemes provide more accurate results compared to existing ones. The comparative analysis of proposed hybrid model with the existing model assures the effectiveness on the parameters of Packet Delivery Ratio (PDR), throughput with less overhead for variation in number of nodes and node speed. Improvements/Applications: The results of MANET routing scenario positively support the effectiveness and performance of our scheme and we can extend the proposed scheme to MANETs with cognitive radios.