Hunting attacks in the dark: clustering and correlation analysis for unsupervised anomaly detection

Summary Network anomalies and attacks represent a serious challenge to ISPs, who need to cope with an increasing number of unknown events that put their networks' integrity at risk. Most of the network anomaly detection systems proposed so far employ a supervised strategy to accomplish their ta...

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Bibliographic Details
Published in:	International Journal of Network Management Vol. 25; no. 5; pp. 283 - 305
Main Authors:	Mazel, Johan, Casas, Pedro, Fontugne, Romain, Fukuda, Kensuke, Owezarski, Philippe
Format:	Journal Article
Language:	English
Published:	Chichester Blackwell Publishing Ltd 01.09.2015 Wiley Wiley Subscription Services, Inc
Series:	Measure, Detect and Mitigate ‐ Challenges and Trends in Network Security
Subjects:	[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] Anomalies Anomaly Correlation Clustering Computer information security Computer Science Correlation analysis Detectors Filtering Rules MAWILab Networking and Internet Architecture Networks Outliers Detection Signatures Traffic engineering Traffic flow Unsupervised Anomaly Detection & Characterization unsupervised anomaly detection & characterization, clustering, outliers detection, anomaly correlation, filtering rules, MAWILab Anomaly Correlation Outliers Detection Unsupervised Anomaly Detection & Characterization Filtering Rules Clustering
ISSN:	1055-7148, 1099-1190
Online Access:	Get full text
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