Publication:
A Comprehensive Model for Securing Sensitive Patient Data in a Clinical Scenario

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dc.contributor.authorLópez Martínez, Antonio
dc.contributor.authorGil Pérez, Manuel
dc.contributor.authorRuiz-Martínez, Antonio
dc.contributor.departmentIngeniería de la Información y las Comunicaciones
dc.date.accessioned2024-02-06T07:54:51Z
dc.date.available2024-02-06T07:54:51Z
dc.date.issued2023-11-30
dc.description©<2023>. This manuscript version is made available under the CC-BY license http://creativecommons.org/licenses/ccby /4.0/ This document is the Published, version of a Published Work that appeared in final form in [IEEE Access]. To access the final edited and published work see [https://doi.org/ 10.1109/ACCESS.2023.3338170]
dc.description.abstractThe clinical environment is one of the most important sources of sensitive patient data in healthcare. These data have attracted cybercriminals who pursue the theft of this information for personal gain. Therefore, protecting these data is a critical issue. This paper focuses on an analysis of the clinical environment, presents its general ecosystem and stakeholders, and inspects the main protocols implemented between the clinical components from a security and privacy perspective. Additionally, this article defines a complete use case to describe the typical workflow within a clinical setting: the life cycle of a patient sample. Moreover, we present and categorize crucial clinical information and divide it into two sensitivity levels: High and Very Sensitive, while considering the severe risks of cybercriminal access. The threat model for the use case has also been identified, in conjunction with the use case’s security and privacy needs. This work served us as basis to develop the minimum security and privacy requirements to protect the use case. Accordingly, we have defined protection mechanisms for each sensitivity level with the enabling technologies needed to satisfy each requirement. Finally, the main challenges and future steps for the use case are presented.es
dc.formatapplication/pdfes
dc.format.extent16es
dc.identifier.citationIEEE Access, vol. 11, pp. 137083-137098, 2023
dc.identifier.doi10.1109/ACCESS.2023.3338170
dc.identifier.issn2169-3536 (electrónico)
dc.identifier.urihttp://hdl.handle.net/10201/138683
dc.languageenges
dc.publisherIEEEes
dc.relationThis work has been partially funded by the strategic project CDL-TALENTUM from the Spanish National Institute of Cybersecurity (INCIBE) and by the Recovery, Transformation and Resilience Plan, Next Generation EUes
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectClinical scenario
dc.subjectPatient data
dc.subjectThreat model
dc.subjectThreat model
dc.subjectPrivacy
dc.subjectSecurity
dc.titleA Comprehensive Model for Securing Sensitive Patient Data in a Clinical Scenarioes
dc.typeinfo:eu-repo/semantics/articlees
dspace.entity.typePublicationes
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