A Bayesian network approach for enhancing security-focused decision support systems

Comunicació presentada a la 2025 IEEE 50th Conference on Local Computer Networks (LCN), celebrada a Sydney (Austràlia) del 13 al 16d'octubre de 2025.

Detalhes bibliográficos
Autores: Fernández-Martínez, Carolina, Siddiqui, Shahbaz, Daza, Vanesa
Formato: capítulo de livro
Estado:Versión aceptada para publicación
Fecha de publicación:2025
País:España
Recursos:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:dnet:rdupf_______::587897a171ab3c74008312d3febbf370
Acesso em linha:https://hdl.handle.net/10230/73617
http://dx.doi.org10.1109/LCN65610.2025.11146363
Access Level:acceso embargado
Palavra-chave:Decision support system
Bayesian networks
Security mechanism
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spelling A Bayesian network approach for enhancing security-focused decision support systemsFernández-Martínez, CarolinaSiddiqui, ShahbazDaza, VanesaDecision support systemBayesian networksSecurity mechanismComunicació presentada a la 2025 IEEE 50th Conference on Local Computer Networks (LCN), celebrada a Sydney (Austràlia) del 13 al 16d'octubre de 2025.The adoption and integration of heterogeneous stacks in most of today’s open-source based networks brings clear benefits like interoperability and availability of advanced features. Yet, on the other hand the increasing number of interconnecting components and moving parts requires maintaining an ever increasing base of interdisciplinary knowledge of different tools in different domains to ensure proper operation. To alleviate such efforts, this work proposes a Decision Support System (DSS) to guide infrastructure operators through the selection of security approaches (e.g. tools) to adopt in their environments. This framework easily captures the end-user high-level requirements on the security triad for different domains and runs inference on the designated models to provide the identified tools (security mechanisms) that better serve such needs. The presented DSS aims at delivering an understandable and extensible framework to accommodate varying requirements and Bayesian Network (BN) models. The architecture and modelling of the system are proposed, aligned with its theoretical framework. Its performance is evaluated in terms of time and prediction accuracy.This work is supported by the AEI-PID2021-128521OB-I00 grant of the Spanish Ministry of Science and Innovation, and Artemisa Chair, an initiative carried out within the framework of the funds of the Recovery, Transformation and Resilience Plan, financed by the European Union (Next Generation), the project of the Spanish Government that traces the roadmap for the modernization of the Spanish economy, the recovery of economic growth and job creation, for the solid, inclusive and resilient economic reconstruction after the COVID-19 crisis, and to respond the challenges of the next decade.Institute of Electrical and Electronics Engineers (IEEE)2026202620252026infoinfo:eu-repo/semantics/bookPartinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/10230/73617http://dx.doi.org10.1109/LCN65610.2025.11146363reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglés2025 IEEE 50th Conference on Local Computer Networks (LCN); 2025 October 13-16; Sydney, Australia. New York: IEEE, 2025.info:eu-repo/grantAgreement/ES/3PE/PID2021-128521OB-I00© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://dx.doi.org/10.1109/LCN65610.2025.11146363info:eu-repo/semantics/embargoedAccessoai:dnet:rdupf_______::587897a171ab3c74008312d3febbf3702026-06-12T07:21:37Z
dc.title.none.fl_str_mv A Bayesian network approach for enhancing security-focused decision support systems
title A Bayesian network approach for enhancing security-focused decision support systems
spellingShingle A Bayesian network approach for enhancing security-focused decision support systems
Fernández-Martínez, Carolina
Decision support system
Bayesian networks
Security mechanism
title_short A Bayesian network approach for enhancing security-focused decision support systems
title_full A Bayesian network approach for enhancing security-focused decision support systems
title_fullStr A Bayesian network approach for enhancing security-focused decision support systems
title_full_unstemmed A Bayesian network approach for enhancing security-focused decision support systems
title_sort A Bayesian network approach for enhancing security-focused decision support systems
dc.creator.none.fl_str_mv Fernández-Martínez, Carolina
Siddiqui, Shahbaz
Daza, Vanesa
author Fernández-Martínez, Carolina
author_facet Fernández-Martínez, Carolina
Siddiqui, Shahbaz
Daza, Vanesa
author_role author
author2 Siddiqui, Shahbaz
Daza, Vanesa
author2_role author
author
dc.subject.none.fl_str_mv Decision support system
Bayesian networks
Security mechanism
topic Decision support system
Bayesian networks
Security mechanism
description Comunicació presentada a la 2025 IEEE 50th Conference on Local Computer Networks (LCN), celebrada a Sydney (Austràlia) del 13 al 16d'octubre de 2025.
publishDate 2025
dc.date.none.fl_str_mv 2025
2026
2026
2026
info
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/acceptedVersion
format bookPart
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/10230/73617
http://dx.doi.org10.1109/LCN65610.2025.11146363
url https://hdl.handle.net/10230/73617
http://dx.doi.org10.1109/LCN65610.2025.11146363
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv 2025 IEEE 50th Conference on Local Computer Networks (LCN); 2025 October 13-16; Sydney, Australia. New York: IEEE, 2025.
info:eu-repo/grantAgreement/ES/3PE/PID2021-128521OB-I00
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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