Lightweight Data-Security Ontology for IoT

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(From the abstract)

Although current estimates depict an steady growth in IoT, many works portrait a yet immature technology in terms of security. Attacks using low performance devices, the application of new technologies and data analysis to infer private data, lack of development in some aspects of security offer a wide field for improvement. The advent of Semantic Technologies to IoT offers a new set of possibilities and challenges, like data markets, aggregators, processors and search engines, which rise the need for security. New regulations, such as GDPR, also call for novel approaches on data-security, covering personal data.

In this work, we present DS4IoT, a data-security ontology for IoT, which covers the representation of data-security concepts with the novel approach of doing so from the perspective of data and introducing some new concepts such as regulations, certifications and provenance, to classical concepts such as access control methods and authentication mechanisms. In the process we followed ontological methodologies, as well as semantic web best practices, resulting in an ontology to serve as a common vocabulary for data annotation, that not only distinguishes itself from previous works on its bottom-up approach, but covers new, current and interesting concepts of data-security, favouring implicit over explicit knowledge representation. Finally, this work is validated by proof of concept, by mapping the DS4IoT ontology to the NGSI-LD data model, in the frame of IoTCrawler EU project.


This paper is an extended version of our paper published in GIOTS conference; “Towards an Ontology for IoT Context-Based Security Evaluation”, presented in Aarhus, Denmark, in June 2019.
Pedro Gonzalez-Gil, Juan Antonio Martinez and Antonio Skarmeta

University of Murcia

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