Soft Computing Techniques for Internet Backbone Traffic Anomaly Detection

Authors:
Antonia Azzini;Matteo Felice;Sandro Meloni;Andrea G. Tettamanzi
Affiliations:
Information Technology Department, University of Milan,;ENEA (Italian Energy New Technology and Environment Agency), and Department of Informatics and Automation, University of Rome "Roma Tre",;Department of Informatics and Automation, University of Rome "Roma Tre",;Information Technology Department, University of Milan,
Venue:
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Year:
2009

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Abstract

The detection of anomalies and faults is a fundamental task for different fields, especially in real cases like LAN networks and the Internet. We present an experimental study of anomaly detection on a simulated Internet backbone network based on neural networks, particle swarms, and artificial immune systems.