Knowledge modelling for automated risk assessment of cybersecurity and indirect patient harms in medical contexts
Knowledge modelling for automated risk assessment of cybersecurity and indirect patient harms in medical contexts
The use of connected medical and in vitro diagnostic devices (CMD&IVD) as part of individual care and self-care practices is growing. Significant attention is needed to ensure that CMD&IVD remain safe and secure throughout their lifecycles — as if a cybersecurity incident were to occur involving these devices, it is possible that in some cases harm may be brought to the person using them. For the effective safety management of these devices, risk assessment is needed that covers both the cybersecurity and patient safety domains. To this end, we present knowledge modelling of indirect patient harms (e.g., misdiagnosis, delayed treatment etc.) resulting from cybersecurity compromises, along with a methodology for encoding these into a previously developed automated cybersecurity risk assessment tool, to begin to bridge the gap between automated risk assessment related to cybersecurity and patient safety.
Automated Risk Assessment, Connected Medical Devices and In Vitro Diagnostic Devices, Cybersecurity, Indirect Patient Harms, Knowledge Modelling, Cyber security
263-274
Senior, Samuel
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Carmichael, Laura
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Taylor, Steve
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Surridge, Mike
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Vilalta, Xavier
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20 February 2025
Senior, Samuel
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Carmichael, Laura
3f71fb73-581b-43c3-a261-a6627994c96e
Taylor, Steve
9ee68548-2096-4d91-a122-bbde65f91efb
Surridge, Mike
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Vilalta, Xavier
76842a50-da86-491d-a41a-d2b5088dbc79
Senior, Samuel, Carmichael, Laura, Taylor, Steve, Surridge, Mike and Vilalta, Xavier
(2025)
Knowledge modelling for automated risk assessment of cybersecurity and indirect patient harms in medical contexts.
Di Pietro, Roberto, Renaud, Kareb and Mori, Paolo
(eds.)
In Proceedings of the 11th International Conference on Information Systems Security and Privacy.
vol. 1,
SciTePress.
.
(doi:10.5220/0013166900003899).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The use of connected medical and in vitro diagnostic devices (CMD&IVD) as part of individual care and self-care practices is growing. Significant attention is needed to ensure that CMD&IVD remain safe and secure throughout their lifecycles — as if a cybersecurity incident were to occur involving these devices, it is possible that in some cases harm may be brought to the person using them. For the effective safety management of these devices, risk assessment is needed that covers both the cybersecurity and patient safety domains. To this end, we present knowledge modelling of indirect patient harms (e.g., misdiagnosis, delayed treatment etc.) resulting from cybersecurity compromises, along with a methodology for encoding these into a previously developed automated cybersecurity risk assessment tool, to begin to bridge the gap between automated risk assessment related to cybersecurity and patient safety.
Text
KnowledgeModellingForIndirectPatientHarms
- Accepted Manuscript
More information
Published date: 20 February 2025
Venue - Dates:
11th International Conference on Information Systems Security and Privacy, , Porto, Portugal, 2025-02-20 - 2025-03-22
Keywords:
Automated Risk Assessment, Connected Medical Devices and In Vitro Diagnostic Devices, Cybersecurity, Indirect Patient Harms, Knowledge Modelling, Cyber security
Identifiers
Local EPrints ID: 499757
URI: http://eprints.soton.ac.uk/id/eprint/499757
PURE UUID: 88c92e66-9d26-46e2-b53b-c83969468c6f
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Date deposited: 03 Apr 2025 16:34
Last modified: 03 Sep 2025 02:02
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Contributors
Author:
Samuel Senior
Author:
Mike Surridge
Author:
Xavier Vilalta
Editor:
Roberto Di Pietro
Editor:
Kareb Renaud
Editor:
Paolo Mori
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