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. 2021 Dec;60(S 02):e89-e102.
doi: 10.1055/s-0041-1735621. Epub 2021 Oct 5.

Towards the Representation of Network Assets in Health Care Environments Using Ontologies

Lucía Prieto Santamaría  1   2 , David Fernández Lobón  2 , Antonio Jesús Díaz-Honrubia  1   2 , Ernestina Menasalvas Ruiz  1   2 , Sokratis Nifakos  3 , Alejandro Rodríguez-González  1   2
Affiliations

Towards the Representation of Network Assets in Health Care Environments Using Ontologies

Lucía Prieto Santamaría et al. Methods Inf Med. 2021 Dec.

Abstract

Objectives: The aim of the study is to design an ontology model for the representation of assets and its features in distributed health care environments. Allow the interchange of information about these assets through the use of specific vocabularies based on the use of ontologies.

Methods: Ontologies are a formal way to represent knowledge by means of triples composed of a subject, a predicate, and an object. Given the sensitivity of network assets in health care institutions, this work by using an ontology-based representation of information complies with the FAIR principles. Federated queries to the ontology systems, allow users to obtain data from multiple sources (i.e., several hospitals belonging to the same public body). Therefore, this representation makes it possible for network administrators in health care institutions to have a clear understanding of possible threats that may emerge in the network.

Results: As a result of this work, the "Software Defined Networking Description Language-CUREX Asset Discovery Tool Ontology" (SDNDL-CAO) has been developed. This ontology uses the main concepts in network assets to represent the knowledge extracted from the distributed health care environments: interface, device, port, service, etc. CONCLUSION: The developed SDNDL-CAO ontology allows to represent the aforementioned knowledge about the distributed health care environments. Network administrators of these institutions will benefit as they will be able to monitor emerging threats in real-time, something critical when managing personal medical information.

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Conflict of interest statement

None declared.

Figures

Fig. 1
Fig. 1
SDNDL-CAO model. SDNDL-CAO, Software Defined Networking Description Language—CUREX Asset Discovery Tool Ontology.
Fig. 2
Fig. 2
Example of a named individual of SDNDL-CAO class device. Triples providing information of the particular device are included in Turtle format ( https://www.w3.org/TR/turtle/ ). SDNDL-CAO, Software Defined Networking Description Language—CUREX Asset Discovery Tool Ontology.
Fig. 3
Fig. 3
Example of a partial visualization of SDNDL-CAO classes (in yellow) and instances (in purple). All the named individuals of class device are represented. The snapshot instance(s) of a particular device individual are included. The visualization has been generated with OntoGraf. The representation is a partial simplification of the complete model and instances. SDNDL-CAO, Software Defined Networking Description Language—CUREX Asset Discovery Tool Ontology.
Fig. 4
Fig. 4
SPARQL query and data returned about VLANs information.
Fig. 5
Fig. 5
SPARQL query and part of the data returned about a given snapshot.
Fig. 6
Fig. 6
SPARQL query and returned data about the devices in which a given service is open.
Fig. 7
Fig. 7
SPARQL query and data returned about devices scanned in multiple snapshots.
See this image and copyright information in PMC

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