  We propose a novel generic trust management framework for crowdsourced IoT
services. The framework exploits a multi-perspective trust model that captures
the inherent characteristics of crowdsourced IoT services. Each perspective is
defined by a set of attributes that contribute to the perspective's influence
on trust. The attributes are fed into a machine-learning-based algorithm to
generate a trust model for crowdsourced services in IoT environments. We
demonstrate the effectiveness of our approach by conducting experiments on
real-world datasets.
