Digital twins in intrusion detection systems based on deep learning

• Опубліковано в: PROBLEMS IN PROGRAMMING
• Дата: 2025
• Випуск: 2
• Сторінки: 20-27
• ISSN: 1727-4907
• Автори та афіліації: O.O. Letychevskyi — Glushkov Institute of Cybernetics NAS of Ukraine; S.O. Yevdokymov — Kherson State University — ORCID: 0000-0001-7213-0259
• Автори: Letychevskyi, O.O., Yevdokymov, S.O.
• Формат: Стаття
• Мова: Англійська
• Опубліковано: PROBLEMS IN PROGRAMMING 2025
• Теми: deep learning; neural network; neurosymbolic approach; digital twins; behavior algebra; UDC 004.056
• Онлайн доступ: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/834
• Назва журналу: Problems in programming

This work aims to improve the accuracy of attack detection in software and hardware systems by utilizing a digital twin in the form of an algebraic model within intrusion detection systems (IDSs) based on deep learning neural networks (DNNs). This approach addresses the shortcomings of training and...