Change-point detection method on 100 Gb/s ethernet interface. - Pavel Benácek; Rudolf B. Blazek; Tomás Cejka; Hana Kubátová (ANCS, 2014)

Stream-wise detection of surreptitious traffic over DNS. - Tomás Cejka; Zdenek Rosa; Hana Kubátová (CAMAD, 2014)

Using Application-Aware Flow Monitoring for SIP Fraud Detection. - Tomás Cejka; Václav Bartos; Lukas Truxa; Hana Kubátová (AIMS, 2015)

Analysis of Vertical Scans Discovered by Naive Detection. - Tomás Cejka; Marek Svepes (AIMS, 2016)

NEMEA: A framework for network traffic analysis. - Tomás Cejka; Václav Bartos; Marek Svepes; Zdenek Rosa; Hana Kubátová (CNSM, 2016)

Building a feedback loop to capture evidence of network incidents. - Zdenek Rosa; Tomás Cejka; Martin Zádník; Viktor Pus (CNSM, 2016)

Configuration of open vSwitch using OF-CONFIG. - Tomás Cejka; Radek Krejcí (NOMS, 2016)

Preserving Relations in Parallel Flow Data Processing. - Tomás Cejka; Martin Zádník (AIMS, 2017)

Hunting SIP Authentication Attacks Efficiently. - Tomás Jánský; Tomás Cejka; Václav Bartos (AIMS, 2017)

Making Flow-Based Security Detection Parallel. - Marek Svepes; Tomás Cejka (AIMS, 2017)

Augmented DDoS Mitigation with Reputation Scores. - Tomás Jánský; Tomás Cejka; Martin Zádník; Václav Bartos (ARES, 2018)

Enhanced Flow Monitoring with P4 Generated Flexible Packet Parser. - Tomás Cejka; Petr Velan; Jirí Havránek; Pavel Benácek (AIMS, 2018)

P4-To-VHDL: Automatic generation of high-speed input and output network blocks. - Pavel Benácek; Viktor Pus; Hana Kubátová; Tomás Cejka (Microprocess. Microsystems, 2018)

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)

Network traffic classification based on periodic behavior detection. - Josef Koumar; Tomás Cejka (CNSM, 2022)

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)

Evaluation of the Limit of Detection in Network Dataset Quality Assessment with PerQoDA. - Katarzyna Wasielewska; Dominik Soukup; Tomás Cejka; José Camacho 001 (PKDD/ECML Workshops (2), 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)

Active Learning Framework to Automate NetworkTraffic Classification. - Jaroslav Pesek; Dominik Soukup; Tomás Cejka (CoRR, 2022)

Active Learning Framework For Long-term Network Traffic Classification. - Jaroslav Pesek; Dominik Soukup; Tomás Cejka (CCWC, 2023)

Look at my Network: An Insight into the ISP Backbone Traffic. - Tomás Benes; Jaroslav Pesek; Tomás Cejka (CNSM, 2023)

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

Enhancing DeCrypto: Finding Cryptocurrency Miners Based on Periodic Behavior. - Josef Koumar; Richard Plný; Tomás Cejka (CNSM, 2023)

Machine Learning Metrics for Network Datasets Evaluation. - Dominik Soukup; Daniel Uhrícek; Daniel Vasata; Tomás Cejka (SEC, 2023)

Unevenly Spaced Time Series from Network Traffic. - Josef Koumar; Tomás Cejka (TMA, 2023)

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

Fine-grained TLS services classification with reject option. - Jan Luxemburk; Tomás Cejka (Comput. Networks, 2023)

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

MFWDD: Model-based Feature Weight Drift Detection Showcased on TLS and QUIC Traffic. - Lukás Jancicka; Dominik Soukup; Josef Koumar; Filip Nemec; Tomás Cejka (CNSM, 2024)

LGBM2VHDL: Mapping of LightGBM Models to FPGA. - Tomás Martínek; Jan Korenek; Tomás Cejka (FCCM, 2024)

Analysis of Statistical Distribution Changes of Input Features in Network Traffic Classification Domain. - Lukás Jancicka; Josef Koumar; Dominik Soukup; Tomás Cejka (NOMS, 2024)

TCI: A system for distributed network monitoring, troubleshooting and dataset creation. - Dominik Soukup; Jaroslav Pesek; Lukás Hejcman; David Benes; Tomás Cejka (NOMS, 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)

Towards Building Network Outlier Detection System for Network Traffic Monitoring. - Josef Koumar; Jaroslav Pesek; Kamil Jerábek; Tomás Cejka (NOMS, 2025)

Interpretable Threat Detection with Evidential Classifier: The MQTT Case. - Jaroslav Pesek; Kensuke Fukuda; Tomás Cejka (NOMS, 2025)

Multichannel Histograms for Flow Classification. - Daniel Poliakov; Kamil Jerábek; Dusan Kolár; Tomás Cejka (NOMS, 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)

Comparative Analysis of Deep Learning Models for Real-World ISP Network Traffic Forecasting. - Josef Koumar; Timotej Smolen; Kamil Jerábek; Tomás Cejka (CoRR, 2025)