Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

A Trust Model for Data Sharing in Smart Cities

Lee, GM (2016) A Trust Model for Data Sharing in Smart Cities. In: Communications (ICC), 2016 IEEE International Conference on . (IEEE ICC 2016, 23 May 2016 - 27 May 2016, Kuala Lumpur, Malaysia).

[img] Text
ICC2016-gmlee-final.pdf - Accepted Version
Restricted to Repository staff only

Download (388kB)

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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Internet of Things; Smart Cities; Trust-based Data Sharing; Data Usage Control; Defeasible Reasoning; Air Pollution Monitoring
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science & Mathematics
Publisher: IEEE
Date Deposited: 02 Mar 2016 13:19
Last Modified: 13 Apr 2022 15:14
URI: https://researchonline.ljmu.ac.uk/id/eprint/3024
View Item View Item