Provenance and Trust as New Factors for Self-Organization in a Wireless Sensor Network

Abstract

Trust can be an important component of wireless sensor networks for believability of the produced data and trust history is a crucial asset in deciding trust of the data. In our previous work, we developed an architecture called ProTru and we showed how provenance can be used for registering previous trust records and other information such as node type, data type, node location, average of historical data. We designed a distributed trust enhancing architecture using only local provenance during sensor fusion with a low communication overhead. Our network is cognitive in the sense that our system reacts automatically upon detecting low trust and restructures itself. In this work, we are extending our previous architecture by storing dataflow provenance graphs. This feature will enhance the cognitive abilities of our system by giving the network the capability of remembering past network snapshots.