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KISS methodologies for network management and anomaly detection
dc.creator | Vega, Carlos | es_ES |
dc.creator | Aracil Rico, Javier | es_ES |
dc.creator | Magaña Lizarrondo, Eduardo | es_ES |
dc.date.accessioned | 2019-08-26T11:13:31Z | |
dc.date.available | 2019-12-03T00:00:17Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | C. Vega, J. Aracil and E. Magana, 'KISS Methodologies for Network Management and Anomaly Detection,' 2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, 2018, pp. 1-6. doi: 10.23919/SOFTCOM.2018.8555785 | en |
dc.identifier.isbn | 9789532900873 | |
dc.identifier.issn | 1847-358X | |
dc.identifier.uri | https://hdl.handle.net/2454/34676 | |
dc.description | Trabajo presentado al 26th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2018. Croacia, 13-15 de septiembre de 2018 | en |
dc.description.abstract | Current networks are increasingly growing in size, complexity and the amount of monitoring data that they produce, which requires complex data analysis pipelines to handle data collection, centralization and analysis tasks. Literature approaches, include the use of custom agents to harvest information and large data centralization systems based on clusters to achieve horizontal scalability, which are expensive and difficult to deploy in real scenarios. In this paper we propose and evaluate a series of methodologies, deployed in real industrial production environments, for network management, from the architecture design to the visualization system as well as for the anomaly detection methodologies, that intend to squeeze the vertical resources and overcome the difficulties of data collection and centralization. | en |
dc.description.sponsorship | The authors would like to thank MINECO, received through grant TEC2015-69417 (TRAFICA). | en |
dc.format.extent | 6 p. | |
dc.format.mimetype | application/pdf | en |
dc.language.iso | eng | en |
dc.publisher | IEEE | en |
dc.relation.ispartof | 2018 26th International Conference on Software, Telecommunications and Computer Networks, Softcom 2018, pp. 181-186 | en |
dc.rights | © 2018 University of Split, FESB. | en |
dc.subject | Anomaly detection | en |
dc.subject | Network management | en |
dc.subject | Computer network security | en |
dc.subject | KISS methodologies | en |
dc.subject | Ccomplex data analysis pipelines | en |
dc.subject | Horizontal scalability | en |
dc.title | KISS methodologies for network management and anomaly detection | en |
dc.type | info:eu-repo/semantics/conferenceObject | en |
dc.type | Contribución a congreso / Biltzarrerako ekarpena | es |
dc.contributor.department | Ingeniería Eléctrica, Electrónica y de Comunicación | es_ES |
dc.contributor.department | Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza | eu |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
dc.embargo.terms | 2019-12-03 | |
dc.identifier.doi | 10.23919/SOFTCOM.2018.8555785 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TEC2015-69417-C2-2-R/ES/ | en |
dc.relation.publisherversion | https://doi.org/10.23919/SOFTCOM.2018.8555785 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | en |
dc.type.version | Versión aceptada / Onetsi den bertsioa | es |