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ORDAIN: An Ontology for Trust Management in the Internet of Things

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10574))

Abstract

The Internet of Things is coming and it has the potential to change our daily life. Yet, such a large scaled environment needs a semantic background to achieve interoperability and knowledge diffusion. Furthermore, this open, distributed and heterogeneous environment raises important challenges, such as trustworthiness among the various types of devices and participants. Developing and sharing ontologies that support trust management models and applications would be an effective step in achieving semantic interoperability on a large scale. Currently, most of the ontologies and semantic description frameworks in the Internet of Things are either context-based or at an early stage. This paper reports on identifying and incorporating social and non-social parameters involved in the Internet of Things in a general-purpose ontology that will support trust management. This ontology will include among others data and semantics about trust principles, involved parties, characteristics of entities, rating parameters, rule-based mechanisms, confidence and dishonesty in the environment. Defining an ontology and using semantic descriptions for data related to trustworthiness issues will provide an important instrument in developing distributed trust (reputation) models.

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Acknowledgments

The Postdoctoral Research was implemented through an IKY scholarship funded by the “Strengthening Post-Academic Researchers/Researchers” Act from the resources of the OP “Human Resources Development, Education and Lifelong Learning” priority axis 6, 8, 9 and co-funded by The European Social Fund - the ESF and the Greek government.

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Correspondence to Kalliopi Kravari .

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Kravari, K., Bassiliades, N. (2017). ORDAIN: An Ontology for Trust Management in the Internet of Things. In: Panetto, H., et al. On the Move to Meaningful Internet Systems. OTM 2017 Conferences. OTM 2017. Lecture Notes in Computer Science(), vol 10574. Springer, Cham. https://doi.org/10.1007/978-3-319-69459-7_15

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  • DOI: https://doi.org/10.1007/978-3-319-69459-7_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69458-0

  • Online ISBN: 978-3-319-69459-7

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