Martin Jureček

I am an Assistant Professor at the Faculty of Information Technology of the Czech Technical University in Prague, Czech Republic. I lead the Cybersecurity and Artificial Intelligence Research Group, which focuses on applying artificial intelligence (AI) and machine learning to cybersecurity and investigating the security and robustness of machine learning models. My research interests include machine learning-based malware detection, adversarial machine learning, concept drift detection, explainable AI, and the robustness of AI systems against adversarial attacks. I have been recognized by Computertrends magazine as one of the Top IT Personalities of the Czech Republic for 2025. I studied cryptology at the Faculty of Mathematics and Physics, Charles University in Prague, and subsequently received my PhD from the Faculty of Information Technology, Czech Technical University in Prague, where my doctoral research focused on artificial intelligence for cybersecurity.

Recent news

New preprints
(7 Oct 2026)
Here is a list of my latest preprints published on arXiv and IACR ePrint: Neural Fingerprints for Malware Analysis: An Image-Based Metric Learning Approach with Application to Cross-Domain Classification with M. Deshagouni, S. Akther and M. Stamp; Image-Based Techniques and Ensemble Soft Voting for Malware Classification with S. R. Lokhande, F. Di Troia and M. Stamp; Concept Drift Detection and Adaptive Retraining of Malware Classification Models with C. W. Berruz Chungata, K. Potika, W. B. Andreopoulos and M. Stamp; CAM-Guided Saliency Cutout and Image-Based Malware Classification with Y. Ebrahimi and M. Stamp; Building an Adversarial Malware Dataset by Family and Type: Generation, Evasion, and Poisoning Evaluation with D. Košťál; Adversarial Malware Generation in Linux ELF Binaries via Semantic-Preserving Transformations with L. Hrdonka; and Comparative Evaluation of Open-Source Gröbner Basis Implementations for Small-Scale AES Polynomial Systems over GF(2) with P. Holý.
Edited book
(10 Sep 2026)
Prof. Mark Stamp, Prof. Andrii Shalaginov, and I have prepared a new book, Artificial Intelligence for Cyber Defense in Emerging Threats (flyer PDF). The book has been submitted and will contain 25 chapters.
Paper presented at SEAA '26
(2 Sep 2026)
The paper Gray-Box Poisoning of Continuous Malware Ingestion Pipelines with J. Dolejš and R. Lórencz has been presented at the 52nd Euromicro Conference Series on Software Engineering and Advanced Applications.
Paper presented at IEEE Big Data Service '26
(27 Jul 2026)
The paper Maximum Mean Discrepancy for Concept Drift Detection in Malware Classification Models with C. W. Berruz Chungata, K. Potika and M. Stamp has been presented at the 12th International Conference on Big Data Computing Service and Machine Learning Applications.
Two papers presented at SECRYPT '26
(16 Jul 2026)
The paper Adversarial Co-Evolution of Malware and Detection Models: A Bilevel Optimization Perspective with O. Jurečková, M. Kozák and R. Lórencz, and the paper Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations with T. Kalný and M. Stamp have been presented at the 12th International Conference on Information Systems Security and Privacy.
Top IT Personality of the Czech Republic 2025 – Recognition by Computertrends
(8 Mar 2026)
The magazine Computertrends, in its 1–2/2026 issue, named me a Top IT Personality in the Czech Republic for 2025.
Two papers presented at ICISSP '26
(6 Mar 2026)
The paper Detecting and Explaining Malware Family Evolution Using Rule-Based Drift Analysis with O. Jurečková, and the paper A Comparison of Selected Image Transformation Techniques for Malware Classification with M. Stamp and his students have been presented at the 12th International Conference on Information Systems Security and Privacy.