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. |