3 papers
cs.LG2025
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…
cs.LG2025
Comparative Analysis of Deep Learning Models for Real-World ISP Network Traffic Forecasting
Josef Koumar, Timotej SmoleÅ, Kamil JeÅábek +1
Accurate network traffic forecasting is essential for Internet Service Providers (ISP) to optimize resources, enhance user experience, and mitigate anomalies. This study evaluates…
cs.LG2024
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting
Josef Koumar, Karel Hynek, Tomáš Äejka +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…