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Публикации

Кушнир Д.В., Шемякин С.Н. Децимация m-последовательностей как способ получения примитивных полиномов. Проблемы информационной безопасности. Компьютерные системы. 2023. № 1 (53). С. 72-78.
Kushnir D., Kovtsur M., Muthanna A., Kistruga A., Akilov M., Batalov A. Developing instrument for investigation of blockchain technology. Studies in Computational Intelligence. 2022. Т. 1030. С. 123-141.
Кушнир Д.В., Шемякин С.Н. Особенности формирования ключевых данных в квантовой криптографической сети. В сборнике: Актуальные проблемы инфотелекоммуникаций в науке и образовании. сборник научных статей: в 4х томах. Санкт-Петербургский государственный университет телекоммуникаций им. проф. М.А. Бонч-Бруевича. Санкт-Петербург, 2021. С. 560-564.
Кушнир Д.В., Шемякин С.Н. Исследование возможных методов аутентификации согласования данных в классическом канале в протоколах квантовой криптографии. Вестник Санкт-Петербургского государственного университета технологии и дизайна. Серия 1: Естественные и технические науки. 2021. № 4. С. 63-67.
Кушнир Д.В. и д.р. Под ред. Ю.В.Арзуманяна. Информационное общество. Инфокоммуникации и бизнес. Учебник с грифом «рекомендовано УМО». СПб.: СПбГУТ, 2005. 480 с.
Korjik, V., Kushnir, D. Key sharing based on the wire-tap channel type II concept with noisy main channel. Lecture Notes in Computer Science/Advances in Cryptology — ASIACRYPT ’96 (Scopus)
Daniel Zelle, Roland Rieke, Christian Plappert, Christoph Kraub, Dmitry Levshun, Andrey Chechulin. SEPAD – Security Evaluation Platform for Autonomous Driving. The 28th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP-2020). Vesteos, Sweden, March 11-13, 2020. P.413-420. DOI: 10.1109/PDP50117.2020.00070. (Scopus, WoS, A2 Qualis)
Dmitry Levshun, Igor Kotenko, Andrey Chechulin. The application of the methodology for secure cyber-physical systems design to improve the semi-natural model of the railway infrastructure // Microprocessors and Microsystems, November 2020, Р. 103482. ISSN 0141-9331. DOI: 10.1016/j.micpro.2020.103482. (Scopus, WoS, Q2)
Левшун Д.С., Гайфулина Д.А., Чечулин А.А., Котенко И.В. Проблемные вопросы информационной безопасности киберфизических систем. Информатика и автоматизация. Т. 19. № 5. 2020. С. 1050-1088. DOI: 10.15622/ia.2020.19.5.6. (Scopus, Q3, RSCI)
Maxim Kolomeets, Olga Tushkanova, Dmitry Levshun, Andrey Chechulin. Camouflaged bot detection using the friend list. Proceedings of the 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). 2021. P. 253-259. DOI: 10.1109/PDP52278.2021.00048. (Scopus, WoS, A2 Qualis)
Dmitry Levshun, Olga Tushkanova, Andrey Chechulin. Active learning approach for inappropriate information classification in social networks. Proceedings of the 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2022). P. 283-289. DOI: 10.1109/PDP55904.2022.00050. URL: https://ieeexplore.ieee.org/document/9756680/ (Scopus, WoS, A2 Qualis)
Diana Gaifulina, Alexander Branitskiy, Dmitry Levshun, Elena Doynikova and Igor Kotenko. Sentiment analysis of social network posts for the detection of potentially destructive impacts. Proceedings of the 15th International Symposium on Intelligent Distributed Computing (IDC-2022). September 14-16, Bremen, Germany. 2023. P. 203-212. DOI: 10.1007/978-3-031-29104-3_23. (Scopus, in list of Top Computer Science Conferences)
Dmitry Vesnin, Dmitry Levshun, Andrey Chechulin. Trademark Similarity Evaluation Using Combination of ViT and Local Features. Information (2023). Vol. 14. No. 7:398. DOI: 10.3390/info14070398 (Scopus, WoS, Q2)
Dmitry Levshun. Comparative analysis of machine learning methods in vulnerability metrics transformation. Proceedings of the 7-th International Scientific Conference "Intelligent Information Technologies for Industry" (IITI-2023). September 25-30, St. Petersburg, Russia. 2023. P. 60-70. DOI: 10.1007/978-3-031-43792-2_6. (Scopus)
Dmitry Levshun, Andrey Chechulin. Vulnerability Categorization for Fast Multistep Attack Modelling. Proceedings of the 33rd Conference of the Open Innovations Association FRUCT. May 24-26, Zilina, Slovakia. 2023. P. 169-175. DOI: 10.23919/FRUCT58615.2023.10143048. (WoS, Scopus)
Dmitry Levshun. Comparative analysis of machine learning methods in vulnerability categories prediction based on configuration similarity. Proceedings of the 16th International Symposium on Intelligent Distributed Computing (IDC-2023). September 13-15, Hamburg, Germany. 2023. P. 231-242. (Scopus, in list of Top Computer Science Conferences)
Dmitry Levshun, Diana Levshun. ion of Machine Learning Methods for Keylogger Detection based on Network Activity. Proceedings of the 16th International Conference on COMmunication Systems & NETworkS (COMSNETS 2024). January 3-7, Bengaluru, India, 2024. P. 19-24. DOI: 10.1109/COMSNETS59351.2024.10427503. (Scopus, A2 Qualis)
Dmitry Levshun, Dmitry Vesnin. Exploring BERT for Predicting Vulnerability Categories in Device Configurations. Proceedings of the 10th International Conference on Information Systems Security and Privacy (ICISSP 2024). February 26-28, Rome, Italy. 2024. P. 452-461. DOI: 10.5220/0012471800003648. (WoS, Scopus, in list of Top Computer Science Conferences)
Vasily Desnitsky, Dmitry Levshun, Andrey Chechulin and Igor Kotenko. Design Technique for Secure Embedded Devices: Application for Creation of Integrated Cyber-Physical Security System. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA). 2016. Vol. 7(2). P. 60-80. URL: https://isyou.info/jowua/papers/jowua-v7n2-4.pdf. (Scopus, Q1)
Dmitry Levshun, Yannick Chevalier, Igor Kotenko, Andrey Chechulin. Design and verification of a mobile robot based on the integrated model of cyber-physical systems. Simulation Modelling Practice and Theory, Vol. 105, 2020. DOI: 10.1016/j.simpat.2020.102151. URL: https://www.sciencedirect.com/science/article/pii/S1569190X20300903. (Scopus, WoS, Q1)
Dmitry Levshun, Andrey Chechulin, Igor Kotenko. Design of secure microcontroller-based systems: application to mobile robots for perimeter monitoring. Sensors 2021. Vol. 21(24). 2021. P. 8451. DOI: 10.3390/s21248451. URL: https://www.mdpi.com/1424-8220/21/24/8451. (Scopus, WoS, Q1)
Dmitry Levshun, Andrey Chechulin, Igor Kotenko. Security and Privacy Analysis of Smartphone-Based Driver Monitoring Systems from the Developer’s Point of View. Sensors 2022. Vol. 22(13). 2022. P. 5063. DOI: 10.3390/s22135063. URL: https://www.mdpi.com/1424-8220/22/13/5063. (Scopus, WoS, Q1)
Dmitry Levshun, Olga Tushkanova, Andrey Chechulin. Two-model active learning approach for inappropriate information classification in social networks. International Journal of Information Security. 2023. DOI: 10.1007/s10207-023-00726-7 (Scopus, WoS, Q1)