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IMC
2005
ACM

Network Anomography

9 years 3 months ago
Network Anomography
Anomaly detection is a first and important step needed to respond to unexpected problems and to assure high performance and security in IP networks. We introduce a framework and a powerful class of algorithms for network anomography, the problem of inferring network-level anomalies from widely available data aggregates. The framework contains novel algorithms, as well as a recently published approach based on Principal Component Analysis (PCA). Moreover, owing to its clear separation of inference and anomaly detection, the framework opens the door to the creation of whole families of new algorithms. We introduce several such algorithms here, based on ARIMA modeling, the Fourier transform, Wavelets, and Principal Component Analysis. We introduce a new dynamic anomography algorithm, which effectively tracks routing and traffic change, so as to alert with high fidelity on intrinsic changes in network-level traffic, yet not on internal routing changes. An additional benefit of dynami...
Yin Zhang, Zihui Ge, Albert G. Greenberg, Matthew
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where IMC
Authors Yin Zhang, Zihui Ge, Albert G. Greenberg, Matthew Roughan
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