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When Simple Model Just Works: Is Network Traffic Classification in Crisis?
Kamil Jerabek, Jan Luxemburk, Richard Plny +3
Machine learning has been applied to network traffic classification (TC) for over two decades. While early efforts used shallow models, the latter 2010s saw a shift toward complex…
Comparative Analysis of Deep Learning Models for Real-World ISP Network Traffic Forecasting
Josef Koumar, Timotej Smoleň, Kamil Jeřábek +1
Accurate network traffic forecasting is essential for Internet Service Providers (ISP) to optimize resources, enhance user experience, and mitigate anomalies. This study evaluates…
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting
Josef Koumar, Karel Hynek, Tomáš Čejka +1
Anomaly detection in network traffic is crucial for maintaining the security of computer networks and identifying malicious activities. One of the primary approaches to anomaly det…
Network Traffic Classification based on Single Flow Time Series Analysis
Josef Koumar, Karel Hynek, Tomáš Čejka
Network traffic monitoring using IP flows is used to handle the current challenge of analyzing encrypted network communication. Nevertheless, the packet aggregation into flow recor…