Agent-based analysis of trustworthiness in wireless sensor networks

Information assurance is a critical component of any organization's data network. Trustworthiness of the sensor data, especially in the case of wireless sensor networks (WSNs), is an important metric for any application that requires situational awareness. In a WSN, information packets are typically not encrypted and the nodes themselves could be located in the open, leaving them susceptible to tampering and physical degradation. In order to develop a method to assess trustworthiness in WSNs, we have utilized statistical trustworthiness metrics and have implemented an agent-based simulation platform that can perform various trustworthiness measurement experiments for various WSN operating scenarios. Different trust metrics are used against multiple vulnerabilities to detect anomalous behavior and node failure as well as malicious attacks. The simulation platform simulates WSNs with various topologies, routing algorithms, battery and power consumption models, and various types of attacks and defense mechanisms. Additionally, we adopt information entropy based techniques to detect anomalous behavior. Finally, detection techniques are fused to provide various metrics, and various trustworthiness metrics are fused to provide aggregate trustworthiness for the purpose of situational awareness.