Ultra High Resolution Jitter Measurement Method for Ethernet Based Networks. - Karel Hynek; Tomás Benes; Matej Bartik; Pavel Kubalík (CCWC, 2019)

FPGA Packet Reflector for Network Path Testing. - Sven Ubik; Karel Hynek; Jiri Melnikov (IWSSIP, 2019)

DoH Insight: detecting DNS over HTTPS by machine learning. - Dmitrii Vekshin; Karel Hynek; Tomás Cejka (ARES, 2020)

Pipelined ALU for effective external memory access in FPGA. - Tomás Benes; Michal Kekely; Karel Hynek; Tomás Cejka (DSD, 2020)

Evaluating Bad Hosts Using Adaptive Blacklist Filter. - Karel Hynek; Tomás Cejka; Martin Zádník; Hana Kubátová (MECO, 2020)

Refined Detection of SSH Brute-Force Attackers Using Machine Learning. - Karel Hynek; Tomás Benes; Tomás Cejka; Hana Kubátová (SEC, 2020)

Detection of HTTPS Brute-Force Attacks with Packet-Level Feature Set. - Jan Luxemburk; Karel Hynek; Tomás Cejka (CCWC, 2021)

Towards Evaluating Quality of Datasets for Network Traffic Domain. - Dominik Soukup; Peter Tisovcík; Karel Hynek; Tomás Cejka (CNSM, 2021)

Novel HTTPS classifier driven by packet bursts, flows, and machine learning. - Zdena Tropková; Karel Hynek; Tomás Cejka (CNSM, 2021)

Large Scale Measurement on the Adoption of Encrypted DNS. - Sebastián García; Karel Hynek; Dmitrii Vekshin; Tomás Cejka; Armin Wasicek (CoRR, 2021)

Tunneling through DNS over TLS providers. - Lukás Melcher; Karel Hynek; Tomás Cejka (CNSM, 2022)

Large Scale Analysis of DoH Deployment on the Internet. - Sebastián García; Joaquín Bogado; Karel Hynek; Dmitrii Vekshin; Tomás Cejka; Armin Wasicek (ESORICS (3), 2022)

DeCrypto: Finding Cryptocurrency Miners on ISP Networks. - Richard Plný; Karel Hynek; Tomás Cejka (NordSec, 2022)

Summary of DNS Over HTTPS Abuse. - Karel Hynek; Dmitrii Vekshin; Jan Luxemburk; Tomás Cejka; Armin Wasicek (IEEE Access, 2022)

Discovering Coordinated Groups of IP Addresses Through Temporal Correlation of Alerts. - Martin Zádník; Jan Wrona; Karel Hynek; Tomás Cejka; Martin Husák (IEEE Access, 2022)

Network Traffic Classification Based on Single Flow Time Series Analysis. - Josef Koumar; Karel Hynek; Tomás Cejka (CNSM, 2023)

DataZoo: Streamlining Traffic Classification Experiments. - Jan Luxemburk; Karel Hynek (SAFE@CoNEXT, 2023)

Encrypted traffic classification: the QUIC case. - Jan Luxemburk; Karel Hynek; Tomás Cejka (TMA, 2023)

DNS Over HTTPS Detection Using Standard Flow Telemetry. - Kamil Jerábek; Karel Hynek; Ondrej Rysavý; Ivana Burgetova (IEEE Access, 2023)

BOTA: Explainable IoT Malware Detection in Large Networks. - Daniel Uhrícek; Karel Hynek; Tomás Cejka; Dusan Kolár (IEEE Internet Things J., 2023)

WIF: Efficient Library for Network Traffic Analysis. - Richard Plný; Karel Hynek; Pavel Siska (CNSM, 2024)

Towards Reusable Models in Traffic Classification. - Jan Luxemburk; Karel Hynek (TMA, 2024)

Comparative analysis of DNS over HTTPS detectors. - Kamil Jerábek; Karel Hynek; Ondrej Rysavý (Comput. Networks, 2024)

NetTiSA: Extended IP flow with time-series features for universal bandwidth-constrained high-speed network traffic classification. - Josef Koumar; Karel Hynek; Jaroslav Pesek; Tomás Cejka (Comput. Networks, 2024)

CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting. - Josef Koumar; Karel Hynek; Tomás Cejka; Pavel Siska (CoRR, 2024)

Lightweight Traffic Classification: A Simple Baseline Matching Deep Learning Performance. - Jaroslav Pesek; Jan Luxemburk; Karel Hynek (TMA, 2025)

Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning Success. - Jan Luxemburk; Karel Hynek; Richard Plný; Tomás Cejka (CoRR, 2025)

When Simple Model Just Works: Is Network Traffic Classification in Crisis? - Kamil Jerábek; Jan Luxemburk; Richard Plný; Josef Koumar; Jaroslav Pesek; Karel Hynek (CoRR, 2025)

Taming Volatility: Stable and Private QUIC Classification with Federated Learning. - Richard Jozsa; Karel Hynek; Adrián Pekár (CoRR, 2025)