The paper focuses on the study of cyber security in Ukraine and creation of a predictive model for reducing the risk of identified cyber threats. Forecasting is performed using a linear regression model, taking into account the optimal dependence of specific threats in the field of cyber security of Ukraine on variables characterizing capabilities / vulnerabilities of cyber security. An unique empirical base was used for the analysis, which was formed on the basis of an expert survey of the cyber security system’s subjects in Ukraine. In order to increase the representativeness of the research, based on the selection of reliable expert population, data cleaning is provided. Methodological research is based on a risk-oriented approach, which provided a risk assessment of the spread of cyber threats and, on this basis, the determination of capabilities / vulnerabilities of the cyber security system in Ukraine. The value of the research is formed not only by assessing the risks of the spread of cyber threats, but by a more in-depth analysis of the dependence of the cyber threats’ level on the vulnerability of the cyber security system based on the search for optimal and statistically significant relationships. The experiment was conducted on the basis of determining the optimal model for forecasting the risk of the spread of one of the most significant threats in Ukraine – data confidentiality breach (54.67%), depending on the variables that characterize the capabilities / vulnerabilities of the cyber security system in Ukraine. The experiment showed that the optimal model emphasizes the predictors characterizing the vulnerability of the organizational cyber security system – "Departmental level of cybersecurity monitoring" and capabilities: "The level of use of risk management approaches at the operational level" and "The level of methodological support for cybersecurity of the critical infrastructure system".
The article discusses the possibility of use of the parent-child relationship questionnaire in a situation of raising a child with developmental disorders in a family. As the basic technique is considered Varga–Stolin parental attitudes questionnaire. The possibility of its modification is discussed changing the number of questions, the contents of which inadequately investigated in the question’s situation, clarification of "Control" scale. This construct changes significantly when relationships of parents with a sick child is considered comparing to the normal family. Also the number of items was reduced. Confirmatory factor analysis was used for psychometric analysis. The study involved 137 parents of children with mental developmental disorders, which are the inmates of children's homes, boarding schools, Centers promote family education Moscow. Funding This work was supported by grant RFH № 16-06-00991.
The process of introducing distance learning into the education system in different countries has its own characteristics. Distance learning is a motivating factor in learning foreign languages, contributes to the achievement of personal, meta subject, subject learning outcomes and, ultimately, the achievement of the goal of teaching foreign languages: the formation of foreign language communicative competence. The specificity of the subject "Foreign language" is primarily due to the fact that the leading component of the content of teaching a foreign language is not the basics of science, but methods of activity are teaching various types of speech activity: speaking, listening, reading and writing. Distance learning contributes to the implementation of modern educational paradigms such as individualization and differentiation of educational activities, self-education and self-development of trainees.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.