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Content Provider | IEEE Xplore Digital Library |
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Author | Lingsong Zhang Zhengyuan Zhu Jeffay, K. Marron, J.S. Smith, F.D. |
Copyright Year | 2008 |
Description | Author affiliation: Dept. of Biostat., Harvard Sch. of Public Health, Boston, MA (Lingsong Zhang) |
Abstract | In the context of Internet traffic anomaly detection, we will show that some outliers in a time series can be difficult to detect at one scale while they are easy to find at another scale. In this paper, we develop an outlier detection method for a time series with long range dependence, and conclude that testing outliers at multiple time scales helps to reveal them. We present a multi-resolution anomaly detection (MRAD) procedure for detecting network anomalies. We show that the MRAD method is useful, especially when outliers appear as a slight local mean level shift with a rather long duration, e.g., as generated by a port scan. A novel MRAD outlier map is proposed to visualize the location of the outliers, and also to suggest the significance probabilities (p values) for them. |
Starting Page | 1 |
Ending Page | 6 |
File Size | 1002227 |
Page Count | 6 |
File Format | |
ISBN | 9781424422197 |
DOI | 10.1109/INFOCOM.2008.4544618 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-04-13 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Visualization Fluid flow measurement Statistical analysis Time series analysis Intrusion detection Telecommunication traffic Time measurement Internet Statistics Testing |
Content Type | Text |
Resource Type | Article |
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