Trust can be an important component of wireless sensor networks for believability of the produced data and historical value is a crucial asset in deciding trust of the data. A node's trust can change over time after its initial deployment due to various reasons such as energy loss, environmental conditions or exhausting sources. Provenance can play a significant role for supporting the calculation of information trust by recording the data flow and snapshots of the network. Furthermore provenance can be used for registering previous trust records and other information such as node type, data type, node location, average of the historical data. We will introduce a node-level trust-enhancing architecture for sensor networks using provenance. Our network will be cognitive in the sense that our system will react automatically upon detecting anomalies. Through simulations we will verify our model and will show that our approach can provide substantial enhancements in information trust as compared to the traditional network approaches. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]