https://sci.ldubgd.edu.ua/jspui/handle/123456789/6428 2026-04-04T10:24:46Z 2026-04-04T10:24:46Z Полотай, О.І. Довганик, С. https://sci.ldubgd.edu.ua/jspui/handle/123456789/15157 2024-12-08T13:20:34Z 2020-01-01T00:00:00Z

Title: SIEM-системи, як елемент аналізу та управління подіями CSOC Authors: Полотай, О.І.; Довганик, С.

2020-01-01T00:00:00Z Belej, O Полотай, О.І. Kolesnyk, K. https://sci.ldubgd.edu.ua/jspui/handle/123456789/10894 2021-07-21T08:05:54Z 2020-01-01T00:00:00Z

Title: Application of neural networks in intrusion monitoring system for wireless sensor networks Authors: Belej, O; Полотай, О.І.; Kolesnyk, K. Abstract: This article has shown the current state of the intrusion detection area and the main areas of research. Network attack detection is currently one of the most significant network technology issues. In addition to active means of repelling attacks, they use network-based intrusion detection systems that scan all network traffic and signal this if any deviations are detected in it. The main problem of network intrusion detection systems is the low detection efficiency of fundamentally new types of intrusions that have not yet been studied and entered into the signature database. To solve the problem of false positives in intrusion detection systems, the authors propose using Bayesian inference algorithms to make decisions about intrusions. In the study, the authors proposed an intrusion detection system model to increase the reliability of intrusion detection using the dynamic Bayesian network model and increase the battery life of the system. The experiments showed a greater efficiency of the proposed system compared to the Snort system for the investigated types of attacks in terms of the ability to detect new intrusions and reduce errors of the first and second kinds.

2020-01-01T00:00:00Z Полотай, О.І. Кухарська, Н.П. Самотий, В.В. Лагун, А.Е. https://sci.ldubgd.edu.ua/jspui/handle/123456789/7540 2021-06-16T05:08:01Z 2020-01-01T00:00:00Z

Title: Using of the trend extrapolation method for qualitative prognosis the global cybersecurity index in Ukraine Authors: Полотай, О.І.; Кухарська, Н.П.; Самотий, В.В.; Лагун, А.Е. Abstract: In the paper, the research problem of cybersecurity in Ukraine and constituent elements of the cybersecurity global index were considered. The study object is the methods of predicting the indicator of the cybersecurity global index in Ukraine based on the trend extrapolation methods using one dynamic sequence. The purpose of the work is to apply predicting methods to build a prediction of the global cybersecurity index in Ukraine. The tasks of the job are to build a global cybersecurity index prediction based on average absolute gain, building a prediction of global cybersecurity index based on the average growth rate, building a prediction of global cybersecurity index based on flowing average, assessing the quality of prediction of each method and comparing them with each other to choose the best one. There was selected an indicator to characterize the state of cybersecurity development in Ukraine - the Global Cybersecurity Index, and a feature of using the global cybersecurity indicator and all the components on which it is built and which form it was described. Also, different values for Ukraine's five-year global cybersecurity index were formed by using official reports generated by the International Telecommunications Union located in Switzerland. Based on data of 2014-2018 years global cybersecurity index projections in Ukraine for 2019 and 2020 years have been developed. The qualitative Global cybersecurity index predicting was considered using the database of simple trend extrapolation methods. This database includes the following methods: a trend extrapolation method based on the average absolute gain, a trend extrapolation method based on the average growth factor, a trend extrapolation method based on flowing average. Also, the method of ex-post predicating to qualitatively and quantitatively compare the results of each method and determine the best of them was implemented and obtained values and made a diagram of possible future events were compared. The obtained results give reason to hope for improvement of the global cybersecurity index in Ukraine, which maintains the provided existing trends in the development of the cybersecurity sector in the country.

2020-01-01T00:00:00Z Полотай, О.І. Belej, Olexander Nestor, Natalia Panchak, Sofiia https://sci.ldubgd.edu.ua/jspui/handle/123456789/7539 2021-06-16T04:48:50Z 2020-01-01T00:00:00Z

Title: Developing a model of cloud computing protection system for the internet of things Authors: Полотай, О.І.; Belej, Olexander; Nestor, Natalia; Panchak, Sofiia Abstract: This article proposes the use of a multi-agent approach when building a model of the cloud computing protection system of the Internet of things based on the reference architecture of cloud computing. It is proposed to build a system for monitoring user behavior in a cloud computing system using an automated model. The selection of a security agent is necessary on the one hand in connection with the increase in the number of commercial enterprises switching to the cloud computing platform, and on the other hand, with the need to protect data and resources on the Internet of things. The article also presents some scenarios for the interaction of actors based on a dedicated security agent. In this case, the security agent performs a controlling and connecting role between all the actors of the model, monitoring and recognizing unauthorized actions both by cloud users of the Internet of things networks and by actors of the cloud computing system of the Internet of things.

2020-01-01T00:00:00Z