A Method for Detecting Compromised Nodes using Modeling and Simulation Statistical En-route Filtering based Wireless Sensor Networks.

Wireless sensor networks are subject to potential threats since sensor nodes are energy-constrained and are deployed in open-collaborative environments. The nodes are easily compromised by adversaries to generate false reports, called false report injection attacks. The false reports cause unnecessary energy consumption in intermediate nodes and cause false alarms in the sink node. To address the attacks, statistical en-route filtering detects the false report in intermediate nodes. Even though the scheme detects the false report, it is difficult to find the compromised nodes. In this paper, we show how the previously proposed context aware architecture can be exploited to detect the compromised nodes within the SEFbased WSN.The experimental results indicate that the proposed models detect the compromised nodes within a specific time.