Martin Mocko

Research areas: machine learning, deep learning, data science, malware detection, malware clustering, phishing

Position: PhD Student

Martin is a research assistant focusing on information security, in particular malware analysis and detection, phishing and malicious behavior. He is also interested in data analysis, machine learning and deep learning. His research currently focuses on clustering of executable files and creating useful representations for machine learning models.

He holds a Master’s degree in Intelligent Systems from the Slovak University of Technology. During his studies, he received the Institute of Informatics at the Slovak Academy of Sciences award for excellent study performance. He is currently a PhD student at KInIT, doing his PhD at the Faculty Of Information Technology, Brno University of Technology.

He has co-operated in research projects with ČSOB bank and CEAi. His Master’s thesis focused on anomaly detection in the bank domain. He is a former member of PeWe (Personalized Web) research group.

Selected Student Supervising

Master:
Gáfrik Andrej – Detection of malicious activities using machine learning methods. Ongoing

Bachelor:
Kabáč Maroš – Time series forecasting using neural networks. Defended 2020