Evaluating the threat to national information security

Yarovenko, Hanna

doi:10.21511/ppm.18(3).2020.17

Cited by 17 publications

(8 citation statements)

References 19 publications

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“…Vol.13, No.4, 2020 A phase picture of the dynamic system regarding the risk of the money laundering risk of the Ukrainian financial institutions is constructed using differential calculations. Namely, they include identifying partial derivatives of the function regarding the dependence of money laundering risk of the Ukrainian financial institutions on its shaping factors, which form the basis for further study of the dynamic stability of the considered system (formula 10) (Yarovenko, 2020;Dean et al, 2017;Kuzmenko et al, 2014). They describe the behavior of the dynamic system of the money laundering risk indicator of the Ukrainian financial institutions 10Thus, a nonlinear approach based on the bifurcation theory allows building a "phase picture" of the money laundering risk of the Ukrainian financial institutions, i.e., to reflect the trajectories on the selected phase space (Vasilyeva et al, 2019;Shkolnyk et al, 2018).…”

Section: Empirical Results and Discussionmentioning

confidence: 99%

Gravitational and intellectual data analysis to assess the money laundering risk of financial institutions

Lyeonov

Żurakowska-Sawa

Kuzmenko

et al. 2020

Journal of International Studies

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The wide variety of schemes to use companies for money laundering, such as oil smuggling, illegal gas sales, misappropriation of the Central Bank refinancing, misappropriation of bank funds and state-owned enterprises, form the research issues. The sample under study includes 102 countries around the world, which are closely monitored by the Financial Action Task Force (FATF) and have different levels of sociopolitical and economic development. The scientific and methodological approach to assess the financial monitoring risk in terms of the use of financial institutions for money laundering is based on the methods of multidimensional static analysis, descriptive, cluster and dispersive data analysis, gravity theory, nonlinear econometric modeling, differential and bifurcation analysis of dynamic nonlinear systems. The result of the study is a developed model of comprehensive risk assessment for the countries' financial institutions for money laundering, which considers grouping of countries by the

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Section: Empirical Results and Discussionmentioning

confidence: 99%

Gravitational and intellectual data analysis to assess the money laundering risk of financial institutions

Lyeonov

Żurakowska-Sawa

Kuzmenko

et al. 2020

Journal of International Studies

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“…As a demo version was used, 12 representatives were selected in each country cluster for the Data Envelopment Analysis. The minimum value of scales in the program was set based on the calculation of Total redundancy, as a share of its value in the total (Yarovenko, 2020b). When determining the minimum weights, it was taken into account that security indicators have an equivalent effect on the index of information security threats.…”

Section: Resultsmentioning

confidence: 99%

DEA-Analysis Of The Effectiveness Of The Country’s Information Security System

Yarovenko

Kuzmenko

Stumpo³

2020

SEC

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The consequences of the fourth industrial revolution caused an increase in the level of computerization and digitalization of society, which led to problems related to the protection of information of individual users, companies and the state as a whole. The aim of this paper is to analyze the effectiveness of the information security system of countries in terms of its ability to counter information threats. Two groups of input indicators were used for this purpose. The first group was formed by 12 indicators of the country’s world development, which were selected from the World Bank database and based on the results of correlation analysis. The second group includes 5 information technology indicators that characterize certain areas of information security: information technology development, digitalization of the country, countries’ commitment to cybersecurity, readiness to counter cyber threats and use the latest information and communication technologies. The country’s information security threat index is used as a starting point. Data from 159 countries of the world for 2018 were taken for the analysis, as for this number of countries and period there is a complete set of data on selected indicators. Country data were considered based on clusters, which allowed the use of 7 groups. The analysis was performed using the analytical tool Frontier Analyst. The study built CRR and BCC models, among which CRR was preferred, which allowed a more critical assessment of the potential of countries. The paper analyzes the structural effectiveness of socio-economic development indicators and information security indicators of countries, considering the current level of the information security threat index. As a result, the following were identified: an increase in government security spending for zero-cluster countries; the need to transform the information technology component for the countries of the first and second clusters; increasing personal protection, strengthening corruption control and legal regulation for third cluster countries; the need for economic growth and higher social standards for the fourth, fifth and sixth clusters. The obtained models allowed us to estimate the maximum level of growth of the information security threat index with the available resource potential of the country. As a result, it was found that the largest increase in the information security threat index is possible due to the existing potential of the countries of the zero and fifth clusters, which will increase the effectiveness of their response to information threats. Keywords: BBC-model, CCR-model, Data Envelopment Analysis, socio-economic development, information, threat, security.

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“…2021), on the stability of the financial sector: banks (Vasileva T. and Lasukova A., 2013) and banking system (Vasilyeva T. et al, 2016;Kuznyetsova A. et al, 2017), other financial intermediaries (Brychko M. et al, 2021;Fedajev A. et al, 2022). The financial instability causes vulnerabilities in national security (Yarovenko, H., 2020;Shpak N. et al, 2020) and investment attractiveness of the country (Moskalenko B. et al, 2022;Kozmenko S. and Vasilyeva T., 2008). The increase in economic security as a component of national security is especially important in post-pandemic times (Kuznyetsova A. et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Structural modelling for assessing the effectiveness of system for countering legalization of illicit money

Lyeonov¹,

Hlawiczka²,

Boyko³

et al. 2022

Journal of International Studies

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The article suggests a scientific and methodological approach to the evaluation of the infrastructural component’s effectiveness in the anti-money laundering system due to digitalization. Structural modelling is the basis for the mentioned approach implementation, which consists of several steps. First, the input data is selected in terms of the effective regulation of the financial services market, law enforcement and judicial activities, and digitalization. Next, the moving average method is used to identify the growth rate of missing values in the available data series. Then, the selection of relevant factors for financial services market regulation, law enforcement activity, judicial activity and digitalization is based on the principal component analysis. After reducing the input array of data to a comparable form, a structural equations system can be constructed to reflect the impact of the digitalization level on the latent integral characteristics of the directions of anti-money laundering work done by regulatory authorities. Finally, the model is checked for adequacy. The result of this research can serve as an information base for further strengthening the digital vector in the development of regulation institutions and law enforcement agencies overseeing the financial services market, as well as for the radical transformation of courts in Ukraine since digitalization currently negatively affects them.

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Evaluating the threat to national information security

Cited by 17 publications

References 19 publications

Gravitational and intellectual data analysis to assess the money laundering risk of financial institutions

Gravitational and intellectual data analysis to assess the money laundering risk of financial institutions

DEA-Analysis Of The Effectiveness Of The Country’s Information Security System

Structural modelling for assessing the effectiveness of system for countering legalization of illicit money

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