Distributive Training can Improve Neural Network Performance based on RL-CNN Architecture. - Dmytro Proskurin; Sergiy Gnatyuk; Madina Bauyrzhan (CPITS II (1), 2021)

Dataset of Cryptographic Algorithms for UAV Image Encryption based on Artificial Neural Networks (short paper). - Sergiy Gnatyuk; Andrew Okhrimenko; Denys Navrotskyi; Dmytro Proskurin; Bohdan Horbakha (CQPC, 2023)

ML-Based Cryptographic Keys Quality Assessment for 5G / 6G Networks Privacy and Security. - Dmytro Proskurin; Sergiy Gnatyuk; Tetiana Okhrimenko; Maksim Iavich (IDAACS, 2023)

Predicting Pseudo-Random and Quantum Random Number Sequences using Hybrid Deep Learning Models. - Dmytro Proskurin; Sergiy Gnatyuk; Tetiana Okhrimenko (MoMLeT+DS, 2023)

Hybrid RNN-CNN-based model for PRNG identification (short paper). - Dmytro Proskurin; Tetiana Okhrimenko; Sergiy Gnatyuk; Dauriya Zhaksigulova; Nataliia Korshun (CQPC, 2024)

Predicting pseudo-random number generator output with sequential analysis. - Dmytro Proskurin; Maksim Iavich; Tetiana Okhrimenko; Okoro Chukwukaelonma; Tetiana Hryniuk (CSDP, 2024)