Mining Graph-Fourier Transform Time Series for Anomaly Detection of Internet Traffic at Core and Metro Networks

Mining Graph-Fourier Transform Time Series for Anomaly Detection of Internet Traffic at Core and Metro Networks

This article proposes a framework to analyse traffic-data processes on a long-haul backbone infrastructure network providing internet services at a national level. This type of network requires low latency and fast speed, which means there is a large demand for research focusing on near real-time de...

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Bibliographic Details
Main Authors: Manuel Herrera, Yaniv Proselkov, Marco Perez-Hernandez, Ajith Kumar Parlikad
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Backbone network
graph signal processing
internet infrastructure
network topology
anomaly detection
time series mining
Online Access:https://ieeexplore.ieee.org/document/9316656/

Internet

https://ieeexplore.ieee.org/document/9316656/

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