  We introduce the concept of adaptive trust in crowdsourced IoT services. It
is a customized fine-grained trust tailored for specific IoT consumers. Usage
patterns of IoT consumers are exploited to provide an accurate trust value for
service providers. A novel adaptive trust management framework is proposed to
assess the dynamic trust of IoT services. The framework leverages a novel
detection algorithm to obtain trust indicators that are likely to influence the
trust level of a specific IoT service type. Detected trust indicators are then
used to build service-to-indicator model to evaluate a service's trust at each
indicator. Similarly, a usage-to-indicator model is built to obtain the
importance of each trust indicator for a particular usage scenario. The
per-indicator trust and the importance of each trust indicator are utilized to
obtain an overall value of a given service for a specific consumer. We conduct
a set of experiments on a real dataset to show the effectiveness of the
proposed framework.
