Персона: Иваненко, Виталий Григорьевич
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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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Иваненко
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Виталий Григорьевич
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- ПубликацияТолько метаданныеResearch on the Vulnerabilities of Urban Video Surveillance Systems(2020) Alfara, A. U. A.; Ivanov, N. S.; Ivanenko, V. G.; Иваненко, Виталий Григорьевич© 2020 IEEE.This article discusses the problem of detecting dark spots in the urban video surveillance system. To identify shortcomings in the work of urban surveillance cameras, machine learning was used, which allowed to solve the problem of visualizing areas that are not in the camera's field of vision. Taking into account the fact that a wide range of video surveillance devices participated in the study: yard, porch video surveillance cameras and surveillance cameras in crowded places, a system was developed consisting of a database and an algorithm that allows you to request information only about the nearest video surveillance devices. This approach to the implementation of the main goal of the study contributed to the creation of an intuitive, user-friendly program that will help identify and eliminate dark spots in the urban video surveillance system.
- ПубликацияТолько метаданныеCombining Deep Learning and Super-Resolution Algorithms for Deep Fake Detection(2020) Ivanov, N. S.; Arzhskov, A. V.; Ivanenko, V. G.; Иваненко, Виталий Григорьевич© 2020 IEEE.Deep Fake is a technique for human image synthesis based on artificial intelligence. In this article is explored the problem of Deep Fake Video content and its detection. Has been gathered information about previous attempts, analyzed methods used by different researches and considered their actuality right now. Basing on results of the discovery was designed strategy to expose Deep Fake videos that combines previous detection methods with super-resolution algorithms. Results of the research were compared with expected, so recommendations and possible way of continuing developments were given.