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Network Centric Traffic Analysis: Network Centric Anomaly Detection and Network Centric Traffic Classification - Couverture souple

Fan, Jieyan

 
9783836492966: Network Centric Traffic Analysis: Network Centric Anomaly Detection and Network Centric Traffic Classification
Couverture souple
ISBN 10 : 3836492962 ISBN 13 : 9783836492966
Editeur : VDM Verlag Dr. Müller, 2008

Synopsis

To provide more reliable and secure Internet service, Internet service providers have more and more interests in network centric traffic analysis. This book considers this issue from two perspectives, which are of ISP's most interest: 1) network centric anomaly detection and 2) network centric traffic classification. In our study on network centric anomaly detection, we designed an edge router based framework to detect anomaly in the first place they enter network; we proposed the so-called two-way matching features, which are effective indicators of network anomalies; and we creatively considered spatial and temporal correlation among edge routers at the same time. To tap the potential profits made by multimedia services, ISPs are of much interest to detect voice and video traffic. Yet, to our best knowledge no existing approaches are available to separate between voice and video. To solve the problem, we creatively applied spectral analysis techniques to extract regularities in multimedia traffic and used minimum distance to subspace as classification metric. Results demonstrate the effectiveness and robustness of our approach.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

To provide more reliable and secure Internet service, Internet service providers have more and more interests in network centric traffic analysis. This book considers this issue from two perspectives, which are of ISP's most interest: 1) network centric anomaly detection and 2) network centric traffic classification. In our study on network centric anomaly detection, we designed an edge router based framework to detect anomaly in the first place they enter network; we proposed the so-called two-way matching features, which are effective indicators of network anomalies; and we creatively considered spatial and temporal correlation among edge routers at the same time. To tap the potential profits made by multimedia services, ISPs are of much interest to detect voice and video traffic. Yet, to our best knowledge no existing approaches are available to separate between voice and video. To solve the problem, we creatively applied spectral analysis techniques to extract regularities in multimedia traffic and used minimum distance to subspace as classification metric. Results demonstrate the effectiveness and robustness of our approach.

Biographie de l'auteur

Jieyan Fan received his Ph.D. in Electrical and Computer Engineering from University of Florida, Gainesville, FL, in 2007. He is now working in Yahoo! Inc. Dapeng Wu received his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA, in 2003. He is now an associate professor in University of Florida.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2008
Langue
anglais
ISBN 10 
3836492962
ISBN 13 
9783836492966
Reliure
Broché
Nombre de pages
96
Coordonnées du fabricant
non disponible
Personne responsable
non disponible