A Trust Model for Data Sharing in Smart Cities

TL;DR

This paper proposes a trust model for data sharing in smart cities, emphasizing transparency and accountability, using semantic technology and defeasible reasoning, validated through an air pollution monitoring prototype.

Contribution

It introduces a trust-based system architecture and mechanisms for transparent data sharing in IoT-enabled smart cities, integrating semantic and reasoning techniques.

Findings

Prototype demonstrates effective trust management in air pollution data sharing.

Semantic and defeasible reasoning enhance transparency and accountability.

System improves trust acceptance among IoT participants.

Abstract

The data generated by the devices and existing infrastructure in the Internet of Things (IoT) should be shared among applications. However, data sharing in the IoT can only reach its full potential when multiple participants contribute their data, for example when people are able to use their smartphone sensors for this purpose. We believe that each step, from sensing the data to the actionable knowledge, requires trust-enabled mechanisms to facilitate data exchange, such as data perception trust, trustworthy data mining, and reasoning with trust related policies. The absence of trust could affect the acceptance of sharing data in smart cities. In this study, we focus on data usage transparency and accountability and propose a trust model for data sharing in smart cities, including system architecture for trust-based data sharing, data semantic and abstraction models, and a mechanism to enhance transparency and accountability for data usage. We apply semantic technology and defeasible reasoning with trust data usage policies. We built a prototype based on an air pollution monitoring use case and utilized it to evaluate the performance of our solution.