Collusion Based Realization of Trust and Reputation Models in Extreme Fraudulent Environment over Static and Dynamic Wireless Sensor Networks

Abstract

We derive a new representation for the collusive sensor nodes when the underlying fraudulent correlated environment has strong influence on wireless sensor networks performance. We have evaluated collusion effect with respect to static (SW) and dynamic (DW) wireless sensor networks to derive the joint resultant. Moreover accuracy, path length, and energy consumption of sensor node operations are also evaluated. Additionally, we emphasized over the satisfaction evaluation for linguistic fuzzy trust and reputation (LFTM) models in the deployed WSN framework. Finally, simulation analysis has been carried out to prove the validity of our proposal. However, collusion for wireless sensor networks seems intractable with the static and dynamic WSNs when varied with specified number of fraudulent nodes in the scenario.