Volume Anomaly Detection in Data Networks: An Optimal Detection Algorithm Vs. the PCA Approach

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Executive Summary

The crucial future role of Internet in society makes of network monitoring a critical issue for network operators in future network scenarios. The Future Internet will have to cope with new and different anomalies, motivating the development of accurate detection algorithms. This paper presents a novel approach to detect unexpected and large traffic variations in data networks. The authors introduce an optimal volume anomaly detection algorithm in which the anomaly-free traffic is treated as a nuisance parameter. The algorithm relies on an original parsimonious model for traffic demands which allows detecting anomalies from link traffic measurements, reducing the overhead of data collection.

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