• Jančička, L., Soukup, D., Koumar, J., Němec, F., & Čejka, T. MFWDD: Model-based Feature Weight Drift Detection Showcased on TLS and QUIC Traffic - Presented at CNSM 2024.

  • Jančička, L., Koumar, J., Soukup, D., & Čejka, T. (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

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

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

  • 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

Workshops, posters, etc

  • K. Jerabek, J. Koumar, D. Poliakov, and J. Pesek, Workshop on AI and and traffic classification, NECS – PhD Winter School, 2024, LINK

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

Preprints

  • J. Koumar, K. Hynek, T. Cejka and P. Šiška, “CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting”. LINK

  • J. Koumar, K. Hynek, J. Pesek, and T. Cejka, “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 Tomas Čejka. “Unevenly Spaced Time Series from Network Traffic.” LINK