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dc.contributor.authorFernández-Arruti Gallego, Pedro
dc.contributor.authorEstévez Pereira, Julio Jairo
dc.contributor.authorNóvoa, Francisco
dc.contributor.authorDafonte, Carlos
dc.contributor.authorFernández, Diego
dc.date.accessioned2022-01-05T12:10:00Z
dc.date.available2022-01-05T12:10:00Z
dc.date.issued2021
dc.identifier.citationFernández-Arruti, P.; Estévez-Pereira, J.J.; Nóvoa, F.J.; Dafonte, J.C.; Fernández, D. Low Cost Automated Security Audit System. Eng. Proc. 2021, 7, 58. https://doi.org/10.3390/engproc2021007058es_ES
dc.identifier.urihttp://hdl.handle.net/2183/29313
dc.descriptionPresented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.es_ES
dc.description.abstract[Abstract] In recent years, a quick transition towards digitization has been observed in most organizations. Along with it, certain inherent problems have appeared, such as the increase in cyber threats. Large organizations are able to adapt easily, but this does not happen with small and medium-sized companies. Currently, there are very few solutions aimed at fulfilling the needs of these small enterprises, so we have worked on a tool for them. Our tool is capable of displaying key, easy-to-interpret information related to each organization’s network assets. To achieve this, we used passive and active analysis techniques and successfully evaluated the viability of using machine learning techniques to get more meaningful information. All of the information obtained is displayed in a simple web application, which is designed to be used by managers in organizations without them needing to handle complex concepts and vocabulary.es_ES
dc.description.sponsorshipCITIC, as a Research Center accredited by the Galician University System, is funded by “Consellería de Cultura, Educación e Universidade from Xunta de Galicia”, supported in an 80% through ERDF, ERDF Operational Programme Galicia 2014–2020, and the remaining 20% by “Secretaría Xeral de Universidades (Grant ED431G 2019/01). This work was also funded by the research consolidation grant ED431B 2021/36, Art.83 collaboration F19/17, the Ministry of Economy and Competitiveness of Spain, and the FEDER funds of the European Union (Project PID2019-111388GB-I00)es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2021/36es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111388GB-I00/ES/DETECCION TEMPRANA DE INTRUSIONES Y ANOMALIAS EN REDES DEFINIDAS POR SOFTWARE/
dc.relation.urihttps://doi.org/10.3390/engproc2021007058es_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectNetwork Audites_ES
dc.subjectPassive análisises_ES
dc.subjectActive análisises_ES
dc.subjectMachine learninges_ES
dc.titleLow Cost Automated Security Audit Systemes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleEngineering Proceedingses_ES
UDC.volume7es_ES
UDC.issue1es_ES
UDC.startPage58es_ES
dc.identifier.doi10.3390/engproc2021007058


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