Abstract
Although current estimates depict steady growth in Internet of Things (IoT), many works portray an as 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 for 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 by 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 the IoTCrawler EU project.
Highlights
As world wide economies are leaning more and more on data as sources of value so does the Internet of Things (IoT) grow
We considered the possibility of integrating concepts from some of the different ontologies described in Section 2, creating a reference implementation that linked to those other concepts, but decided against it; the reason being that they describe in different levels of detail some of the concepts that we capture in DS4IoT, the underlying meaning is fundamentally different and could lead to inference problems and representation mismatches
A number of security ontologies, some of which are aimed at the IoT scenery, were studied in Section 2, none are aimed at, or can be used for, the task of annotating functional data-security aspects from the standpoint of data itself
Summary
As world wide economies are leaning more and more on data as sources of value so does the Internet of Things (IoT) grow. Threat Report [3], warn us about an increase in IoT attacks, such as the famous Mirai [4] bot-net, showed us that security, even in the case of apparently harmless devices with very reduced computing power and storage capability that did not produce, or whose produced data was not even deemed to hold any kind of strategic value in IT warfare (such as public ip cameras and DSL routers) cannot be overlooked. This is because by sheer number, those devices can be used to produce some of the strongest attacks ever recorded. Perhaps disturbing is the fact that modern approaches to data
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