期刊
IEEE TRANSACTIONS ON SERVICES COMPUTING
卷 15, 期 4, 页码 2396-2409出版社
IEEE COMPUTER SOC
DOI: 10.1109/TSC.2021.3052219
关键词
Internet of Things; Crowdsourcing; Trust management; Computational modeling; Task analysis; Wireless fidelity; Performance evaluation; Trust; crowdsourcing; internet of things; IoT services
资金
- Australian Research Council [DP160103595, LE180100158]
- Australian Research Council [LE180100158] Funding Source: Australian Research Council
This study proposes a novel generic trust management framework for crowdsourced IoT services, which uses a multi-perspective trust model to capture their inherent characteristics and generates a trust model through a machine learning algorithm.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据