SDN-CF: Traffic classification in SDN ONOS controller using machine learning models

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UDC.coleccionInvestigación
UDC.departamentoCiencias da Computación e Tecnoloxías da Información
UDC.grupoInvTelemática
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación
UDC.journalTitleSoftwareX
UDC.startPage102382
UDC.volume32
dc.contributor.authorCarneiro, Víctor
dc.contributor.authorÁlvarez, M. A.
dc.contributor.authorCacheda, Fidel
dc.date.accessioned2025-10-02T08:50:19Z
dc.date.available2025-10-02T08:50:19Z
dc.date.issued2025-12
dc.descriptionPermanent link to code/repository used for this code version: https://github.com/ElsevierSoftwareX/SOFTX-D-25-00379
dc.description.abstract[Abstract]: SDN-CF (Software-Defined Network - Classification Framework) is a modular Java-based application built on the Northbound API of the ONOS Software-Defined Network (SDN) controller for network traffic analysis using machine learning techniques. While it employs the Random Forest algorithm by default, its open design allows the integration of alternative classifiers. SDN-CF enables the dynamic blocking of unwanted connections and generates an annotated dataset of OpenFlow traffic, supporting reproducible research in anomaly detection. Designed for academic and experimental use in virtualized environments, the tool fosters the evaluation and development of novel detection approaches in SDN contexts.
dc.description.sponsorshipThis work was carried out at CITIC, within the framework of the project PID2023-150794OB-I00, funded by the Ministry of Science, Innovation and Universities (MICIU) and the State Research Agency (AEI) /10.13039/501100011033, and co-funded by the European Regional Development Fund (ERDF), European Union. CITIC, accredited as a center of excellence within the Galician University System and a member of the CIGUS Network, also receives support from the Department of Education, Science, Universities, and Vocational Training of the Xunta de Galicia, co-financed by the EU through the ERDF Galicia 2021–2027 programme (Ref. ED431G 2023/01).
dc.description.sponsorshipXunta de Galicia; ED431G 2023/01
dc.identifier.citationV. Carneiro-Diaz, M.A. Álvarez-González, and F. Cacheda-Seijo, "SDN-CF: Traffic classification in SDN ONOS controller using machine learning models", SoftwareX, Vol. 32, Dec. 2025, 102382, https://doi-org.accedys.udc.es/10.1016/j.softx.2025.102382
dc.identifier.doi10.1016/j.softx.2025.102382
dc.identifier.issn2352-7110
dc.identifier.urihttps://hdl.handle.net/2183/45865
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-150794OB-I00/ES/MEJORANDO LA DETECCION DE CIBER AMENAZAS USANDO MODELOS DE LENGUAJE DE GRAN TAMAÑO PARA PROTOCOLOS DE RED
dc.relation.urihttps://doi-org.accedys.udc.es/10.1016/j.softx.2025.102382
dc.rightsAttribution-NonCommercial 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectSDN
dc.subjectONOS
dc.subjectMachine learning
dc.subjectFlow classification
dc.titleSDN-CF: Traffic classification in SDN ONOS controller using machine learning models
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication652c136c-eea5-4a78-947c-538b1c99f81b
relation.isAuthorOfPublication66ff8e1a-a945-4d02-bc89-7fa42c7947fe
relation.isAuthorOfPublication63253cd0-b4ea-402a-b158-84417c75846a
relation.isAuthorOfPublication.latestForDiscovery652c136c-eea5-4a78-947c-538b1c99f81b

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