In 2025:

  • Josef Koumar, Karel Hynek, Tomáš Čejka, and Pavel Šiška. “CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting” - Accepted to Nature Scientific Data.

  • Josef Koumar, Jaroslav Pešek, Kamil Jeřábek, and Tomáš Čejka. “Towards Building Network Outlier Detection System for Network Traffic Monitoring” - Will be Presented at NOMS 2025.

  • Kamil Jeřábek, Josef Koumar, Jiří Setinský, and Jaroslav Pešek. “Explainable Anomaly Detection in Network Traffic Using LLM” - Submitted to GAIN NOMS 2025.

In 2024:

  • Lukáš Jančička, Dominik Soukup, Josef Koumar, Filip Němec, and Tomáš Čejka. “MFWDD: Model-based Feature Weight Drift Detection Showcased on TLS and QUIC Traffic” - In 2024 20th International Conference on Network and Service Management (CNSM). LINK

  • Lukáš Jančička, Josef Koumar, Dominik Soukup, and Tomáš Čejka. (2024, May). Analysis of Statistical Distribution Changes of Input Features in Network Traffic Classification Domain. In NOMS 2024-2024 IEEE Network Operations and Management Symposium (pp. 1-4). IEEE. LINK

  • Josef Koumar, Karel Hynek, Jaroslav Pešek, and Tomáš Čejka. “NetTiSA: Extended IP flow with time-series features for universal bandwidth-constrained high-speed network traffic classification” Computer Networks, 2024, 110147. DOI: doi.org/10.1016/j.comnet.2023.110147 LINK

In 2023:

  • Josef Koumar, Karel Hynek, and Tomáš Čejka. “Network Traffic Classification based on Single Flow Time Series Analysis.” 2023 19th International Conference on Network and Service Management (CNSM). IEEE, 2023. LINK

  • Josef Koumar, Richard Plný, and Tomáš Čejka. “Enhancing DeCrypto: Finding Cryptocurrency Miners based on Periodic Behavior” 2023 19th International Conference on Network and Service Management (CNSM). IEEE, 2023. LINK

  • Josef Koumar, and Tomáš Čejka. “Unevenly Spaced Time Series from Network Traffic.” 2023 7th Network Traffic Measurement and Analysis Conference (TMA). IEEE, 2023. LINK

  • Jaroslav Pešek, Richard Plný, Josef Koumar, Kamil Jeřábek, and Tomáš Čejka, Augmenting Monitoring Infrastructure For Dynamic Software-Defined Networks, 2023 8th International Conference on Smart and Sustainable Technologies, 2023, LINK

In 2022:

  • Josef Koumar, and Tomáš Čejka. “Network traffic classification based on periodic behavior detection.” 2022 18th International Conference on Network and Service Management (CNSM). IEEE, 2022. LINK

Datasets

  • Josef Koumar, Karel Hynek, Tomáš Čejka, and Pavel Šiška. “CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting” LINK

  • Josef Koumar, Karel Hynek, Jaroslav Pešek, and Tomáš Čejka. “Network traffic datasets with novel extended IP flow called NetTiSA flow” LINK

  • Josef Koumar, Karel Hynek, and Tomáš Čejka. “Network traffic datasets created by Single Flow Time Series Analysis” LINK

  • Josef Koumar, Richard Plný, and Tomáš Čejka. “CESNET-MINER22-TS: Periodic Behavior Features of Cryptomining Communication” LINK

  • Josef Koumar, and Tomáš Čejka. “CESNET-USTS23: a benchmark dataset of Unevenly spaced time series from network traffic” LINK

Workshops, posters, etc

  • Kamil Jerabek, Josef Koumar, Jaroslav Pesek, and Jiří Setinský, Workshop on Anomaly Detection in Network Traffic Using Forecasting, NECS – PhD Winter School, 2025, LINK

  • Kamil Jerabek, Josef Koumar, Daniel Poliakov, and Jaroslav Pesek, Workshop on AI and and traffic classification, NECS – PhD Winter School, 2024, LINK

  • Josef Koumar and Tomáš Čejka. “Detection and recognition of periodic communication in network traffic” 2022, LINK

Preprints

  • Josef Koumar, Karel Hynek, Tomáš Čejka and Pavel Šiška, “CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting”. LINK

  • Josef Koumar, Karel Hynek, Jaroslav Pešek, and Tomáš Čejka, “NetTiSA: Extended IP Flow with Time-series Features for Universal Bandwidth-constrained High-speed Network Traffic Classificatio”. LINK

  • Josef Koumar, Karel Hynek, and Tomáš Čejka. “Network Traffic Classification based on Single Flow Time Series Analysis.” LINK

  • Josef Koumar, and Tomáš Čejka. “Unevenly Spaced Time Series from Network Traffic.” LINK