Our research interest spans multiple areas. We draw from our broad experience from successful research projects and collaborations with academia, industry, and government partners.
We gather knowledge of new cyber threats and train security professionals in correct and timely responses to these threats. We research innovative methods for learning cybersecurity skills, such as games and cyber defense exercises, from which we analyze data about learners’ interactions.
- ŠVÁBENSKÝ Valdemar and Jan VYKOPAL. Challenges Arising from Prerequisite Testing in Cybersecurity Games. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE). Baltimore, USA: ACM, 2018. p. 56-61. DOI: 10.1145/3159450.3159454. (CORE A)
- ŠVÁBENSKÝ Valdemar, Jan VYKOPAL, Milan ČERMÁK and Martin LAŠTOVIČKA. Enhancing Cybersecurity Skills by Creating Serious Games. In Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE). Larnaca, Cyprus: ACM, 2018. p. 194-199. DOI: 10.1145/3197091.3197123. (CORE A)
We develop virtualized, controlled, and monitored environments to provide complex simulations of cyber systems and networks. These environments are further used for research and development of new security methods and tools, as well as cybersecurity education.
- VYKOPAL Jan, Radek OŠLEJŠEK, Pavel ČELEDA, Martin VIZVÁRY and Daniel TOVARŇÁK. KYPO Cyber Range: Design and Use Cases. In Proceedings of the 12th International Conference on Software Technologies (ICSOFT). Madrid, Spain: SciTePress, 2017. p. 310-321. DOI: 10.5220/0006428203100321. (CORE B)
- VYKOPAL Jan, Martin VIZVÁRY, Radek OŠLEJŠEK, Pavel ČELEDA and Daniel TOVARŇÁK. Lessons Learned from Complex Hands-on Defence Exercises in a Cyber Range. In 2017 IEEE Frontiers in Education Conference (FIE). Indianapolis, USA: IEEE, 2017. p. 1-8. DOI: 10.1109/FIE.2017.8190713. (CORE B)
We focus on technologies enabling security analyses over big data. We research mechanisms for intrusion/anomaly detection and malware mitigation through data acquisition, collaborative analysis, information sharing, and automated decision support.
- HUSÁK Martin, Jana KOMÁRKOVÁ, Elias BOU-HARB and Pavel ČELEDA. Survey of Attack Projection, Prediction, and Forecasting in Cyber Security. IEEE Communications Surveys and Tutorials, 2019. ISSN 1553-877X. DOI: 10.1109/COMST.2018.2871866. (D1, IF=20.230)
- REHÁK Martin, Michal PĚCHOUČEK, Martin GRILL, Jan STIBOREK, Karel BARTOŠ and Pavel ČELEDA. Adaptive Multiagent System for Network Traffic Monitoring. IEEE Intelligent Systems, 2009, vol. 24, No 3, p. 16-25. ISSN 1541-1672. DOI: 10.1109/MIS.2009.42. (D1, IF=3.144)
We aim to reliably measure and analyze network data to understand current and emerging threats. We research ways to generate, collect, and analyze large volumes of data in ever-evolving networks.
- JIRSÍK Tomáš, Milan ČERMÁK, Daniel TOVARŇÁK and Pavel ČELEDA. Toward Stream-Based IP Flow Analysis. IEEE Communications Magazine, 2017, vol. 55, No 7, p. 70-76. ISSN 0163-6804. DOI: 10.1109/MCOM.2017.1600972. (D1, IF=9.270)
- HOFSTEDE Rick, Pavel ČELEDA, Brian TRAMMELL, Idilio DRAGO, Ramin SADRE, Anna SPEROTTO and Aiko PRAS. Flow Monitoring Explained: From Packet Capture to Data Analysis with NetFlow and IPFIX. IEEE Communications Surveys and Tutorials, 2014, vol. 16, No 4, p. 2037-2064. ISSN 1553-877X. DOI: 10.1109/COMST.2014.2321898. (D1, IF=6.806)