A network fault diagnostic approach based on a statistical traffic normality prediction algorithm

Jiang, J; Papavassiliou, S

dc.contributor.author	Jiang, J	en
dc.contributor.author	Papavassiliou, S	en
dc.date.accessioned	2014-03-01T02:49:18Z
dc.date.available	2014-03-01T02:49:18Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34480
dc.subject	Anomaly Detection	en
dc.subject	Early Detection	en
dc.subject	Fault Recovery	en
dc.subject	Network Traffic	en
dc.subject	Statistical Properties	en
dc.subject	Traffic Prediction	en
dc.subject	Dynamic Threshold	en
dc.title	A network fault diagnostic approach based on a statistical traffic normality prediction algorithm	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/GLOCOM.2003.1258768	en
heal.identifier.secondary	http://dx.doi.org/10.1109/GLOCOM.2003.1258768	en
heal.publicationDate	2003	en
heal.abstract	Early detection of network failures and performance degradations is a key to rapid fault recovery and robust networking, and has been receiving increasing attention lately. In this paper we present a fault diagnostic methodology, based on the characterization of the dynamic statistical properties of traffic normality in order to detect network anomalies. Anomaly detection is based on the concept that	en
heal.journalName	Global Telecommunications Conference, . GLOBECOM . IEEE	en
dc.identifier.doi	10.1109/GLOCOM.2003.1258768	en