Hybrid method for detecting atypical behavior of users of information and educational systems based on Digital Traces analysis
Year: 2026
Type: article
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.
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $115
OpenAlex ID: W7172051043