Розломій, Інна (orcid.org/0000-0001-5065-9004), Хотунов, Владислав (orcid.org/0000-0002-2093-1270) and Науменко, Сергій (orcid.org/0000-0002-6337-1605) (2025) Chapter XVII. Artificial Intelligence in Identifying Information Security Threats in Cloud-Based Educational Environments (1). ІЦО НАПН України, м. Київ, Україна. ISBN 978-617-8330-53-8
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Abstract
The article presents an approach to detecting information security threats in cloud-based educational environments using artificial intelligence methods. The architecture of a typical cloud platform is described, and key threat categories are classified, including authentication attacks, data integrity violations, confidentiality breaches, and internal risks. An intelligent model for detecting anomalous user behavior was proposed, applying machine learning algorithms such as decision trees, multilayer perceptrons, and gradient boosting. A dataset of user activity logs was prepared, followed by preprocessing, class balancing, and feature normalization. Evaluation of accuracy, recall, specificity, and F1-score demonstrated the superiority of the proposed approach compared to traditional signature-based IDS. The paper provides recommendations for integrating the model into existing learning management systems such as Moodle and Google Classroom, along with outlining technical and organizational conditions for deployment. The proposed solution is scalable, adaptive, and suitable for practical implementation under the resource constraints of educational institutions.
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