|
Title:
|
Detecting network performance anomalies with contextual anomaly detection
|
|
Author:
|
Dimopoulos, Giorgos; Barlet Ros, Pere; Dovrolis, Constantine; Leontiadis, Ilias
|
|
Other authors:
|
Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors; Universitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla |
|
Abstract:
|
Network performance anomalies can be defined as abnormal and significant variations in a network's traffic levels. Being able to detect anomalies is critical for both network operators and end users. However, the accurate detection without raising false alarms can become a challenging task when there is high variance in the traffic. To address this problem, we present in this paper a novel methodology for detecting performance anomalies based on contextual information. The proposed method is compared with the state of the art and is evaluated with high accuracy on both synthetic and real network traffic. |
|
Abstract:
|
Peer Reviewed |
|
Subject(s):
|
-Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica
-Computer networks -- Security measures
-Data protection
-Computer network security
-Feature extraction
-Security of data
-Ordinadors, Xarxes d' -- Mesures de seguretat
-Protecció de dades |
|
Rights:
|
|
|
Document type:
|
Article - Submitted version
Conference Object |
|
Published by:
|
Institute of Electrical and Electronics Engineers (IEEE)
|
|
Share:
|
|
