Trust management for distributed decision fusion in sensor networks

In this paper we investigate how trust, with its various notions and forms, impacts the gathering and fusing of raw data, and its subsequent conversion to knowledge in sensor network. In particular, we study how the presence of compromised or faulty sensors affects the performance of the decision fusion, by using metrics of quality of information (QoI). We first provide analytical frameworks to model the malicious behavior of compromised sensors. We then introduce reputation mechanisms to address the threat of compromised sensors and the management of the trust. Via analysis and simulation, we evaluate how the reputation mechanisms can improve the performance of the fusion process. The end results provide valuable insight into the dynamics of the interplay between information networks, communication networks, as well as decision making support in social-cognitive networks.