Abstract
A Supply chain in the era of the Internet of Industrial Things faces new challenges in terms of modelling. The challenges stem from a number of characteristics like scalability, dependency and dynamism. In this paper, we introduce an ontology-enhanced method for modelling assets and their dependency in the context of supply chains. This method enables us to infer new insights from the domain. It also provides a dynamic knowledge representation and reasoning by capturing all aspects of supply chains from three different perspectives including business, asset, and sector. The results show that the proposed method can address the challenges by utilizing ontology and synching three relevant perspectives. Moreover, the developed ontology (OntoCyrene) is rich enough to bring light to the dark angles of the modelled scenarios. The theme chosen for this work is cyber security and we used real-world scenarios derived from the Cyrene (Cyrene EU H2020 Project is available at: https://www.cyrene.eu.) project to populate and evaluate the ontology.
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Notes
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- 2.
The Rule Mark-up Initiative can be accessible at: www.ruleml.org.
- 3.
Semantic web Rule Language accessible at: www.w3.org/Submission/SWRL.
- 4.
SPARQL is accessible at: https://www.w3.org/TR/rdf-sparql-query/.
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Available at: https://www.protege.stanford.edu
- 6.
Centro Ricerche Fiat (CRF) is one of the main private research centre in Italy. Available at: https://www.crf.it/
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Heydari, M., Mouratidis, H., Tafreshi, V.H.F. (2023). OntoCyrene: Towards Ontology-Enhanced Asset Modelling for Supply Chains in the Context of Cyber Security. In: Katsikas, S., et al. Computer Security. ESORICS 2022 International Workshops. ESORICS 2022. Lecture Notes in Computer Science, vol 13785. Springer, Cham. https://doi.org/10.1007/978-3-031-25460-4_9
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