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DEVELOPMENT OF A LABORATORY WORKSHOP ON ANALYSIS AND DETECTION OF RANKING PROGRAMS FOR CYBERSECURITY EDUCATIONAL PROGRAMS

Nataliia Kitsel, Oksana Borysenko · Cybersecurity Education Science Technique · 2026

The article addresses the issue of insufficient practical training of cybersecurity students in analyzing and detecting ransomware, which remains one of the most dangerous and rapidly evolving types of malicious software. Modern ransomware samples employ advanced encryption mechanisms, extensive command-and-control infrastructures, built-in anti-analysis techniques, and capabilities for bypassing traditional security tools. Consequently, effective specialist training requires not only theoretical knowledge but also well-developed practical skills in using static and dynamic analysis tools, behavioral threat detection methods, models for classifying malicious activity, machine learning and deep learning techniques, as well as EDR and SIEM systems in the context of real cyber incidents. The purpose of the study is to develop a laboratory practicum that provides comprehensive immersion into the processes of ransomware analysis and detection, contributing to the formation of the professional competencies required in the field of cyber defense. The paper substantiates the structure and content of laboratory tasks covering the analysis of the ransomware attack lifecycle, investigation of

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