Design and implementation of tools to build an ontology of Security Requirements for Internet of Medical Things

• URL: http://arxiv.org/abs/2501.03067v1
• Date: Mon, 06 Jan 2025 15:04:45 GMT
• Title: Design and implementation of tools to build an ontology of Security Requirements for Internet of Medical Things
• Authors: Daniel Naro, Jaime Delgado, Silvia Llorente, Amanda Palomo,
• Abstract summary: In the Internet of Medical Things (IoMT) world, manufacturers or third parties must be aware of the security requirements expressed by both laws and specifications. An ontology charting the relevant laws and specifications (for the European context) is very useful. Due to the very high number and size of the considered specification documents, we have put in place a methodology and tools to simplify the transition from natural text to an ontology.
• Score: 2.446672595462589
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• Abstract: When developing devices, architectures and services for the Internet of Medical Things (IoMT) world, manufacturers or integrators must be aware of the security requirements expressed by both laws and specifications. To provide tools guiding through these requirements and to assure a third party of the correct compliance, an ontology charting the relevant laws and specifications (for the European context) is very useful. We here address the development of this ontology. Due to the very high number and size of the considered specification documents, we have put in place a methodology and tools to simplify the transition from natural text to an ontology. The first step is a manual highlighting of relevant concepts in the corpus, then a manual translation to XML/XSD is operated. We have developed a tool allowing us to convert this semi-structured data into an ontology. Because the different specifications use similar but different wording, our approach favors the creation of similar instances in the ontology. To improve the ontology simplification through instance merging, we consider the use of LLMs. The responses of the LLMs are compared against our manually defined correct responses. The quality of the responses of the automated system does not prove to be good enough to be trusted blindly, and should only be used as a starting point for a manual correction.

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