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Erschienen in: Journal of Network and Systems Management 2/2007

01.06.2007

Anomaly Detection Aiming Pro-Active Management of Computer Network Based on Digital Signature of Network Segment

verfasst von: Bruno Bogaz Zarpelão, Leonardo de Souza Mendes, Mario Lemes Proença Jr.

Erschienen in: Journal of Network and Systems Management | Ausgabe 2/2007

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Abstract

Detecting anomalies accurately is fundamental to rapid diagnosis and repair of problems. This paper proposes a novel Anomaly detection system based on the comparison of real traffic and DSNS (Digital Signature of Network Segment), generated by BLGBA (Baseline for Automatic Backbone Management) model, within a hysteresis interval using the residual mean and on the correlation of the detected deviations. Extensive experimental results on real network servers confirmed that our system is able to detect anomalies on the monitored devices, avoiding the high false alarms rate.

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Metadaten
Titel
Anomaly Detection Aiming Pro-Active Management of Computer Network Based on Digital Signature of Network Segment
verfasst von
Bruno Bogaz Zarpelão
Leonardo de Souza Mendes
Mario Lemes Proença Jr.
Publikationsdatum
01.06.2007
Erschienen in
Journal of Network and Systems Management / Ausgabe 2/2007
Print ISSN: 1064-7570
Elektronische ISSN: 1573-7705
DOI
https://doi.org/10.1007/s10922-007-9064-y

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