Network traffic anomaly detection

"Diagnosing unusual events (called "anomalies") in a large-scale network like Internet Service Providers and enterprise networks is critical and challenging for both network operators and end users," explain Hiroyuki Kasai from The University of Electro-Communications in Japan, and co-authors Wolfgang Kellerer Martin Kleinsteuber at the Technical University of Munich in Germany in a recent report. In their latest work they devise a computationally efficient and effective algorithm to identify network level anomalies by exploiting the state-of-the-art machine learning algorithms, especially the large-scale higher-order tensor tracking technique.

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