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Content Provider | IEEE Xplore Digital Library |
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Author | Yang Liu Linfeng Zhang Yong Guan |
Copyright Year | 2010 |
Abstract | Internet has become an essential part of the daily life for billions of users worldwide, who are using a large variety of network services and applications everyday. However, there have been serious security problems and network failures that are hard to resolve, for example, botnet attacks, polymorphic worm/virus spreading, DDoS, and flash crowds. To address many of these problems, we need to have a network-wide view of the traffic dynamics, and more importantly, be able to detect traffic anomalies in a timely manner. Spatial analysis methods have been proved to be effective in detecting network-wide traffic anomalies that are not detectable at a single monitor. To our knowledge, Principle Component Analysis (PCA) is the best-known spatial detection method for the coordinated low-profile traffic anomalies. However, existing PCA-based solutions have scalability problems in that they require linear running time and space to analyze the traffic measurements within a sliding window, which makes it often infeasible to be deployed for monitoring large-scale high-speed networks. We propose a sketch-based streaming PCA algorithm for the network-wide traffic anomaly detection in a distributed fashion. Our algorithm only requires logarithmic running time and space at both local monitors and Network Operation Centers (NOCs), and can detect both high-profile and coordinated low-profile traffic anomalies with bounded errors. |
Starting Page | 807 |
Ending Page | 816 |
File Size | 918532 |
Page Count | 10 |
File Format | |
ISBN | 9781424472611 |
ISSN | 10636927 |
e-ISBN | 9781424472628 |
DOI | 10.1109/ICDCS.2010.45 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-06-21 |
Publisher Place | Italy |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Principal component analysis Telecommunication traffic Monitoring IP networks Web and internet services Spatial resolution Scalability Time measurement Large-scale systems High-speed networks Data Streams Traffic Anomaly Principle Component Analysis |
Content Type | Text |
Resource Type | Article |
Subject | Computer Networks and Communications Hardware and Architecture Software |
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