7 citations · 7 across the 5 of their papers we have counts for
6 papers
CESNET-TimeSeries26: A Multi-Year Network Traffic Time Series Dataset for Annual Seasonality, Concept Drift, and Long-Term Anomaly Detection
Josef Koumar, Karel Hynek, Kamil Jerabek +1
Forecast-based models are fundamental to network traffic management and anomaly detection. However, it is essential to evaluate these forecasting models over extended periods of ti…
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…
Data Protection and Security Issues With Network Error Logging
Libor Polčák, Kamil Jeřábek
Network Error Logging helps web server operators detect operational problems in real-time to provide fast and reliable services. This paper analyses Network Error Logging from two…
Network Error Logging: HTTP Archive Analysis
Kamil Jeřábek, Libor Polčák
Network Error Logging helps web server operators detect operational problems in real-time to provide fast and reliable services. HTTP Archive provides detail information of histori…
Measurement and characterization of DNS over HTTPS traffic
Kamil Jerabek, Ondrej Rysavy, Ivana Burgetova
Domain name system communication may provide sensitive information on users' Internet activity. DNS-over-TLS and DNS-over-HTTPS are proposals aiming at increasing the privacy of In…