Кафедра безпеки інформаційних технологій (БІТ)
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Перегляд Кафедра безпеки інформаційних технологій (БІТ) за автором "Balagura, D. S."
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Публікація Analysis and comparison of data protection protocols of Wi-Fi networks(2022) Balagura, D. S.; Karavaiev, V. М.Публікація Applications of Generative AI and Large Language Models in network and cloud security(ХНУРЕ, 2025) Nadtochyi, M. M.; Balagura, D. S.The aim of the paper is to analyze theory and practice of GenAI and LLM applications in network and cloud security.Публікація Comparative Analysis of the Performance of RSA,ECDSA, and CRYSTALS-Dilithium Digital Signature Algorithms in the Post-Quantum Era(2025) Tovma, O. M.; Balagura, D. S.The development of quantum computing poses unprecedented challenges to modern cryptographic infrastructures, as Shor’s algorithm can efficiently solve integer factorization and discrete logarithm problems underlying RSA and ECDSA. This paper presents a comparative performance analysis of three key digital signature algorithms - RSA, ECDSA, and CRYSTALS- Dilithium - in the context of transitioning to post-quantum cryptography. The study evaluates the time required for key generation, signature creation, and signature verification. Results demonstrate that the Dilithium algorithm, standardized by NIST in 2022, provides high computational efficiency and strong resistance to quantum attacks, making it suitable for practical implementation in future secure systems.Публікація Аpplications of generative ai and large language models in network and cloud security(ХНУРЕ, 2025) Nadtochyi, M. M.; Balagura, D. S.The aim of the paper is to analyze theory and practice of GenAI and LLM applications in network and cloud security. The scientific exploration of generative AI in network security consistently reveals its dual potential. While it significantly enhances defensive capabilities, it also presents a powerful tool that can be leveraged by attackers. This creates a continuous cycle of innovation, often referred to as a cybersecurity "arms race", where advancements in defensive AI are met by increasingly sophisticated AI-driven attacks