Hybrid Method for Detecting Atypical Behavior of Users of Information and Educational Systems based on Digital Traces Analysis

Authors

  • Olena Kryvoruchko National University of Life and Environmental Sciences of Ukraine, Kyiv
  • Miroslav Lakhno National University of Life and Environmental Sciences of Ukraine, Kyiv
  • Elizaveta Zavhorodnya State University of Trade and Economics, Kyiv
  • Yaroslav Shestak State University of Trade and Economics, Kyiv
  • Valerii Lakhno National University of Life and Environmental Sciences of Ukraine, Kyiv
  • Bauyrzhan Tynymbayev Al-Farabi Kazakh National University
  • Oleksii Savon State University of Trade and Economics, Kyiv

Abstract

The study presents a hybrid multi-level method for analysing the digital traces of users of information and educational systems (IES) in higher education institutions, aimed at detecting atypical behaviour and assessing information-security risks. The method integrates hierarchical structuring of event processes, graph-cluster analysis of interactions, and behavioural risk assessment based on a hybridisation of machine-learning models. The use of real event logs made it possible to demonstrate the method’s effectiveness in detecting risk-related deviations that cannot be identified using existing tools for monitoring user behaviour in information and educational systems in higher education institutions.

Additional Files

Published

2026-07-17

Issue

Vol. 72 No. 3 (2026)

Section

Applied Informatics

License

Copyright (c) 2026 International Journal of Electronics and Telecommunication

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