Context-Aware Trustworthy Service Evaluation in Social Internet of Things

In Social Internet of Things (SIoT) environments, a large number of users and Internet of Things (IoT) based devices are connected to each other, so that they can share SIoT-based services. IoT-based devices establish social relations with each other according to the social relations of their owners...

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Bibliographic Details
Published inService-Oriented Computing Vol. 11236; pp. 129 - 145
Main Authors Khani, Maryam, Wang, Yan, Orgun, Mehmet A., Zhu, Feng
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2018
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
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ISBN9783030035952
3030035956
ISSN0302-9743
1611-3349
DOI10.1007/978-3-030-03596-9_9

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Summary:In Social Internet of Things (SIoT) environments, a large number of users and Internet of Things (IoT) based devices are connected to each other, so that they can share SIoT-based services. IoT-based devices establish social relations with each other according to the social relations of their owners in Online Social Networks (OSNs). In such an environment, a big challenge is how to provide trustworthy service evaluation. Currently, the prevalent trust management mechanisms consider QoS-based trust and social-relation based trust mechanisms in evaluating the trustworthiness of service providers. However, the existing trust management mechanisms in SIoT environments do not consider the different contexts of trust. Therefore, dishonest SIoT devices, based on their owners’ social relations, can succeed in advertising low-quality services or exploiting maliciously provided services. In this paper, we first propose three contexts of trust in SIoT environments including the status and environment (time and location) of devices, and the types of tasks. Then, we propose a novel Mutual Context-aware Trustworthy Service Evaluation (MCTSE) model. The experiments demonstrate that our proposed contextual trust evaluation model can effectively differentiate honest and dishonest devices and provide a high success rate in selecting the most trustworthy services and providing high resilience against different attacks from dishonest devices.
ISBN:9783030035952
3030035956
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-03596-9_9