Lightweight DataSecurity Ontology for IoT 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 datasecurity, covering personal data. In this work, we present DS4IoT, a datasecurity ontology for IoT, which covers the representation of datasecurity 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 bottomup approach, but covers new, current and interesting concepts of datasecurity, favouring implicit over explicit knowledge representation. Finally, this work is validated by proof of concept, by mapping the DS4IoT ontology to the NGSILD data model, in the frame of the IoTCrawler EU project.

Cutting a Path Through the IoT Ontology Jungle  A MetaSurvey Interoperability of InternetofThings(IoT) applications, being characterized by massive heterogeneity of xe2x80x9cthingsxe2x80x9d, has become a key challenge in IoT research due to the omnipresence of smart devices. In order to achieve adequate interoperability levels, semantic technologies in terms of ontologies are a promising paradigm. Due to the plethora of IoT ontologies available, one gets, however, easily lost in the ontology jungle due to the lack of an overall and uptodate view on the IoT ontology landscape. In this respect, the aim of this paper is to act as an umbrella across several uptodate IoT ontology survey papers in terms of a metasurvey comprising a threefold contribution: Firstly, addressing the survey landscape, we provide insight into commonalities and differences regarding the scope of eight survey papers and their rationale behind. Secondly, addressing the IoT ontology landscape, we analyze the IoT ontologies discussed in the survey papers on basis of quantitative and qualitative aspects. Thirdly, addressing the stateofresearch of ontologies for IoT, we identify commonalities and differences regarding conclusions and lessons learned of the survey papers.