A trust evaluation framework for sensor readings in body area sensor networks

This paper addresses a framework to evaluate trustworthiness of a Body Area Sensor Networks (BASN), in particular, of sensor readings. We show that such trustworthiness is to be interpreted with respect to a certain statement or goal; its evaluation is based on quality aspects derived from observations and opinions from others. We examine relevant quality aspects of sensor readings which correspond to potential deviating behaviors of sensors. We then look at how to derive such qualities from observations taking uncertainty into the evaluation as well as decay over time. We develop an extension of subjective logic for this purpose and we show how we can compute quality properties without storing long time series. We then demonstrate this for two examples, including Galvanic Skin Response (GSR) and Electrocardiography (ECG) sensed data.