In this work, we design and demonstrate the feasibility of an innovative reputation-based framework rooted in rigorous statistical theory and belief theory to characterize the trustworthiness of individual nodes in a wireless sensor network (WSN). The resulting mechanism allows the detection of compromised nodes as well as misbehaving nodes. Moreover, trusted querying is enabled by filtering out “untrustworthy sensor nodes and data” and returning the most-trusted aggregate response. We showcase the effectiveness of the proposed framework through a simulation based study.