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In this paper we present an efficient trust-aware in-network aggregation approach for resilient wireless sensor networks. The work is motivated from the well studied reputation and trust relations in the field of social sciences. In our approach, the trust evaluation mechanism is applied to identify trustworthiness of sensor nodes, distinguish illegal/misbehaving nodes, and filter out bogus data in the aggregation process. The objective of this effort is to return the highest-fidelity possible response to the user, while monitoring the health of the network by flagging suspected compromised nodes. The experimental results demonstrate the effectiveness of the proposed approach.