Regardless of whether sensors are used just for observations or as the basis for actual responses, the trustworthiness of sensor data becomes critical when important decisions are based upon these data. Unlike traditional networked systems, sensor networks also take measurements of physical phenomena. Traditional information assurance, which focuses on the integrity of data, does not cover all of the sources of errors that might arise in sensing data. In fact, sensor data can be corrupted at the environmental level, whether through a natural loss of calibration or through a deliberate perturbation of the measurement environment by an adversary. These sources of errors, which affect the process of measurement (PoM), are unique to sensor networks and cannot be addressed through the usual network-centric methods. Hence, to complement traditional information assurance services, defense mechanisms are needed to protect the sensor network from PoM errors. Only when a trust wrapper surrounds sensor measurements should applications make decisions or take actions with important implications.
The proposed research consists of two aspects: corruption research and assurance research. For the former, the team will conduct a thorough threat analysis by cataloging the set of PoM errors that may be introduced for a variety of different sensors. For the latter, the team will augment the existing programming stack for sensor networks by developing a suite of measurement assurance tools.
Developing methods that give sensor networks a natural immunity to PoM errors will allow sensor applications to have a greater chance for success and wider spread use.
