Multi-Perspective Trust Management Framework for Crowdsourced IoT Services

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.