.png){kind=icon}
.png){kind=icon}
Return
Multi-Perspective Trust Management Framework for Crowdsourced IoT Services
.png){kind=icon}
OA
AI
DOI：10.1109/TSC.2021.3052219.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Internet of Things
Crowdsourcing
Trust management
Computational modeling
Task analysis
Wireless fidelity
Performance evaluation
Trust
crowdsourcing
internet of things
IoT services
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.8
Papers:
2.1K
Citations:
6.5K