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dc.contributor.authorBlanco Bueno, Carlos 
dc.contributor.authorSantos Olmo, Antonio
dc.contributor.authorSánchez Crespo, Luis Enrique
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2024-05-09T13:38:17Z
dc.date.available2024-05-09T13:38:17Z
dc.date.issued2024-04
dc.identifier.issn2078-2489
dc.identifier.otherPID2021-124502OB-C42es_ES
dc.identifier.otherPCI2023-145980-2es_ES
dc.identifier.otherTED2021-130355B-C33
dc.identifier.urihttps://hdl.handle.net/10902/32785
dc.description.abstractAs the Internet of Things (IoT) becomes more integral across diverse sectors, including healthcare, energy provision and industrial automation, the exposure to cyber vulnerabilities and potential attacks increases accordingly. Facing these challenges, the essential function of an Information Security Management System (ISMS) in safeguarding vital information assets comes to the fore. Within this framework, risk management is key, tasked with the responsibility of adequately restoring the system in the event of a cybersecurity incident and evaluating potential response options. To achieve this, the ISMS must evaluate what is the best response. The time to implement a course of action must be considered, as the period required to restore the ISMS is a crucial factor. However, in an environmentally conscious world, the sustainability dimension should also be considered to choose more sustainable responses. This paper marks a notable advancement in the fields of risk management and incident response, integrating security measures with the wider goals of sustainability and corporate responsibility. It introduces a strategy for handling cybersecurity incidents that considers both the response time and sustainability. This approach provides the flexibility to prioritize either the response time, sustainability or a balanced mix of both, according to specific preferences, and subsequently identifies the most suitable actions to re-secure the system. Employing a quantum methodology, it guarantees reliable and consistent response times, independent of the incident volume. The practical application of this novel method through our framework, MARISMA, is demonstrated in real-world scenarios, underscoring its efficacy and significance in the contemporary landscape of risk management.es_ES
dc.description.sponsorshipThis work has been developed within the ALBA-UCLM(TED2021-130355B-C31, id.4809130355- 130355-28-521), ALBA-UC (TED2021-130355B-C33, id.3611130630-130630-28-521), AETHER-UCLM (PID2020-112540RB-C42), PRESECREL (PID2021-124502OB-C42), MESIAS (2022-GRIN-34202) and Di4SPDS (PCI2023145980-2) funded by MCIN/AEI/10.13039/501100011033 and Unión Europea Next Generation EU/PRTR.es_ES
dc.format.extent17 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceInformation, 2024, 15(4), 181es_ES
dc.subject.otherCybersecurityes_ES
dc.subject.otherSustainabilityes_ES
dc.subject.otherIncident responsees_ES
dc.subject.otherQuantum programminges_ES
dc.subject.otherQuantum annealinges_ES
dc.titleQISS: Quantum-Enhanced Sustainable Security incident handling in the IoTes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps:// doi.org/10.3390/info15040181es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124502OB-C42/ES/MODELOS Y PLATAFORMAS PARA SISTEMA INFORMATICOS INDUSTRIALES PREDECIBLES, SEGUROS Y CONFIABLES/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PCI2023-145980-2/ES/DISTRIBUTED INTELLIGENCE FOR ENHANCING SECURITY AND PRIVACY OF DECENTRALISED AND DISTRIBUTED SYSTEMS/es_ES
dc.identifier.DOI10.3390/info15040181
dc.type.versionpublishedVersiones_ES


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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Excepto si se señala otra cosa, la licencia del ítem se describe como © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).