Multi-Perspective Trust Management Framework for Crowdsourced IoT Services
This addresses trust management for users and providers in IoT crowdsourcing, but appears incremental as it builds on existing trust modeling approaches.
The authors tackled the problem of managing trust in crowdsourced IoT services by proposing a multi-perspective trust management framework, demonstrating its effectiveness through experiments on real-world datasets.
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.