Research of the Neural Network Module for Detecting Anomalies in Network Traffic. - Yurii Klots; Vira Titova; Nataliia Petliak; Viktor Cheshun; Abdel-Badeeh M. Salem (IntelITSIS, 2022)

Evaluation of the efficiency of the system for detecting malicious outgoing traffic in public networks. - Yurii Klots; Nataliia Petliak; Vira Titova (DESSERT, 2023)

Signature-based approach to detecting malicious outgoing traffic. - Nataliia Petliak; Yurii Klots; Vira Titova; Viktor Cheshun; Artem Boyarchuk (IntelITSIS, 2023)

Attack detection system based on network traffic analysis by means of fuzzy inference. - Nataliia Petliak; Yurii Klots; Vira Titova; Abdel-Badeeh M. Salem (AdvAIT, 2024)

Machine Learning system for detecting malicious traffic generated by IoT devices. - Yurii Klots; Nataliia Petliak; Serhii Martsenko; Vitaliy Tymoshchuk; Ievgen Bondarenko (CITI, 2024)

Detection of network attacks in cyber-physical systems using a rule-based logical neural network. - Vira Titova; Yurii Klots; Viktor Cheshun; Nataliia Petliak; Abdel-Badeeh M. Salem (ICyberPhyS, 2024)

Explainable Deep Learning for Interpretable Brain Tumor Diagnosis from MRI Images. - Eduard Manziuk; Olexander Barmak; Iurii Krak; Nataliia Petliak; Zhenzhen Jin; Pavlo Radiuk (ISDMCI (1), 2024)