Reference : KISS Methodologies for Network Management and Anomaly Detection
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/47674
KISS Methodologies for Network Management and Anomaly Detection
English
Vega Moreno, Carlos Gonzalo mailto [Universidad Autonoma de Madrid > Escuela Politecnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones > > ; Naudit HPCN]
Aracil, Javier [Universidad Autónoma de Madrid > Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones > > ; Naudit HPCN]
Magaña, Eduardo []
2018
KISS Methodologies for Network Management and Anomaly Detection
Vega Moreno, Carlos Gonzalo mailto
Aracil, Javier
Magaña, Eduardo
IEEE
99-104
Yes
International
978-9-5329-0087-3
2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
from 13-09-2018 to 15-09-2018
University of Split, FESB and Croatian Communications and Information Society (CCIS)
Split
Croatia
[en] Network management; anomaly detection carlos.vega@naudit.es javier.aracil@naudit.es eduardo.magana@naudit.es MINECO [TEC2015-69417] The authors would like to thank MINECO ; received through grant TEC2015-69417 (TRAFICA) 22 0 0 0 BL7GB ISI:000454983700019
[en] 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.
http://hdl.handle.net/10993/47674
26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), CROATIA, SEP 13-15, 2018
Proceedings Paper

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