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Quality of Information as an indicator of Trust in the Internet of Things

Baqa, H, Truong, NB, Cresi, N, Lee, GM and Le Gall, F Quality of Information as an indicator of Trust in the Internet of Things. In: IEEE TrustCom-18, 31 July 2018 - 03 August 2018, New York, USA. (Accepted)

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Abstract

The past decade has seen a rise in complexity and scale of software systems, particularly with the emerging of the Internet of Thing consisting of large scale and heterogeneous entities which results in difficulties in providing trustworthy services. To overcome such challenges, providing high quality information for IoT service provider as well as monitoring trust relationship of end-users toward the services are paramount. Such trust relationships are user-oriented and subjective phenomenon that hook on specific quality of data. Following this catalyst, we propose a mechanism to evaluate quality of information (QoI) for streaming data from sensor device; then use the QoI evaluation score as an indicator of trust. Concepts and assessment methodology for QoI along with a trust monitoring system are described. We also develop a framework that classifies streaming of data based on semantic context and generate QoI score as a relevant input for a trust monitoring component. This framework enables a dynamic trust management in the context of IoT for both end-users and services that empowers service providers to deliver trustworthy and high quality IoT services. Challenges encountered during implementation and contribution in standardization are discussed. We believe this paper offers better understanding on QoI and its importance in trust evaluation in IoT applications; also provides detailed implementation of the QoI and Trust components for real-world applications and services.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Quality of Information; Semantics; Trust; Knowledge; Reputation; Experience; Linked Data
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: IEEE
Date Deposited: 22 May 2018 09:14
Last Modified: 22 May 2018 09:20
URI: http://researchonline.ljmu.ac.uk/id/eprint/8689

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