Real time anomaly detection in network traffic time series
Sergio Martínez Tagliafico, Gastón García González, Alicia Fernández, Gabriel Gómez, José Acuña
ITISE 2018 : International conference on Time Series and Forecasting, Granada, Spain, 19-21 sep, page 1--12- 2018
Research group(s):  Tratamiento de Imagenes (gti), Analisis de Redes, Trafico y Estadisticas de Servi (art)
Department(s):  Procesamiento de Señales, Telecomunicaciones
Download the publication : MGFGA18.pdf [2.9MB]  


Anomaly detection is a relevant field of study for many applications and contexts. In this paper we focus in on-line anomaly detection on unidimensional time series provided by different network operator equipments. We have implemented two detection methods, we have optimized them for on-line processing and we have adapted them for integration into a testbed of a well known Hadoop big data platform. We have analyzed the behavior of both methods for the particular datasets available but we also have applied the methods to a publicly available labeled datasets obtaining good results.

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» Sergio Martínez Tagliafico
» Gastón García González
» Alicia Fernández
» Gabriel Gómez
» José Acuña