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From Personal Experience to Global Reputation for Trust Evaluation in the Social Internet of Things

Truong, NB, Um, TW, Zhou, B and Lee, GM From Personal Experience to Global Reputation for Trust Evaluation in the Social Internet of Things. In: IEEE GLOBECOM 2017, 04 December 2017 - 08 December 2017, Singapore. (Accepted)

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Trust has been exploring in the era of Internet of Things (IoT) as an extension of the traditional triad of security, privacy and reliability for offering secure, reliable and seamless communications and services. It plays a crucial role in supporting IoT entities to reduce possible risks before making decisions. However, despite a large amount of trust-related research in IoT, a prevailing trust evaluation model has been still debatable and under development. In this article, we clarify the concept of trust in the Social Internet of Things (SIoT) ecosystems and propose a comprehensive trust model called REK that incorporates third-party opinions, experience and direct observation as the three Trust Indicators. As the convergence of the IoT and social network, the SIoT enables any types of entities (physical devices, smart agents and services) to establish their own social networks based on their owners relationships. We leverage this characteristic for inaugurating Experience and Reputation, which are originally two concepts from social networks, as the two paramount indicators for trust. The Experience and Reputation are characterized and modeled using mathematical analysis along with simulation experiments and analytical results. We believe our contributions offer better understandings of trust models and evaluation mechanisms in the SIoT environment, particularly the two Experience and Reputation models. This paper also opens important trust-related research directions in near future.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Trust; Social Internet of Things; REK Trust Model; Reputation; Experience; Knowledge
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: IEEE
Date Deposited: 08 Sep 2017 10:13
Last Modified: 13 Apr 2022 15:15
URI: https://researchonline.ljmu.ac.uk/id/eprint/7067
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