Hanna Yarovenko

An effective strategy for managing the national information security with capabilities to resist information threats significantly impacts its further development. This study aims to assess the level of threat to the information security of countries based on the integral index. It is proposed to use five indicators characterizing individual areas of information security and 37 world development indicators, selected from the World Bank database. Correlation analysis selected 12 out of 37 development indicators relevant to security indicators for which the correlation coefficient exceeded 0.5 or –0.5. The Harrington-Mencher function is proposed to determine the information security threat index. Nonlinear normalization was carried out to bring the initial data to a comparable measurement. Canonical analysis was performed to determine the indicator weights. The data from 159 countries were taken for 2018 to assess the index. The result was presented on the map showing countries’ distribution by the information security threat index, thus forming five groups. The group with a “very well” resistance to threats includes economically developed countries with a high level of information security. The “well” group was formed by new industrial and developing countries with economic potential sufficient to prevent information threats and combat their consequences. The information security level in developing countries, where the results of overcoming information threats will affect the economic sphere, is defined as “acceptable”. Countries with a low level of development and information security formed groups designated as “bad” and “very bad”, which indicates a high level of threats to their information security.

Acknowledgment
This work is carried out with in the tax payer – funded researches: No. 0118U003574 “Cybersecurity in the banking fraud enforcement: protection of financial service consumers and the financial and economic security growth in Ukraine”.

Type of the article: Research Article

Abstract
Digital technologies have become a key driver of economic growth, competitiveness, and social inclusion, while significant disparities in digital development persist across national economies. The aim of this study is to map and interpret the trajectories of digital transformation in 30 selected European countries (EU member states, associated economies, and Ukraine) during 2011–2022. The study employs the self-organizing map (SOM) with Ward hierarchical clustering to uncover latent structures of digital development, using a balanced panel of 20 indicators across three domains: ICT sector development, digital infrastructure, and digital technology adoption and skills. Cluster validity was assessed via the Elbow Method, Silhouette Coefficient, Calinski-Harabasz, and Davies-Bouldin indices. Results indicate that the two-cluster solution is statistically robust, while the three-cluster solution provides additional insight into transitional patterns of digital transformation. The two-cluster solution revealed a clear distinction between digital leaders and less advanced economies, with the greatest disparities observed in online banking (71% vs. 29%), online purchases (68% vs. 32%), and e-government use (68% vs. 34%). The three-cluster solution provided further nuance, showing that in 2011 most European economies were concentrated in the weakest cluster, while only Northern Europe achieved high levels of digitalization. By 2020, all European countries had reached at least the middle cluster, reflecting a shift from strong polarization toward a more balanced distribution of digital development. Despite progress, structural gaps remain, emphasizing the need for policies that advance digital skills, encourage inclusive adoption, and build trust in online services to sustain digital transformation.

Acknowledgment
The authors acknowledge with gratitude the financial support provided by the Ministry of Education and Science of Ukraine for the research project “Cybersecurity and digital transformations of the country’s wartime economy: the fight against cybercrime, corruption and the shadow sector”, state registration number 0124U000544).

Type of the article: Research Article

Abstract
The study develops a framework for forecasting conflict-related socio-economic vulnerabilities in a cross-country sample using indicators of armed conflict risk, forced displacement, and illicit practices. The analysis uses panel data covering 135 countries over 2012–2024. The Conflict Risk Index, Refugee Load Index, and Cyber Vulnerability Index were constructed using standardized indicators and Principal Component Analysis. The Cyber Vulnerability Index is a proxy for digital exposure to cyber-related disruptions. First-difference panel regressions identified associations between conflict- and migration-related risks and socio-economic indicators. Separately, GRU neural networks were applied to forecast these indicators, while comparative quartile-based ablation and scenario-based perturbation analyses assessed the contribution and sensitivity of corruption, AML-related risk, and cyber vulnerability across country groups. Regression analysis showed that the Conflict Risk Index was statistically associated with deterioration in GDP, GDP per capita, GDP per capita growth, political stability, life expectancy, labor force dynamics, and migration balance. The Refugee Load Index was associated with positive net migration alongside weaker economic growth and lower political stability in host countries. Forecasting results were heterogeneous: adding corruption, AML-related risk, and cyber vulnerability indicators improved accuracy for several targets, but deteriorated performance for some variables and showed evidence of overfitting for GDP per capita in the conflict-risk specification. In high-conflict-risk countries, the largest forecast improvements were for life expectancy (61.02%), GDP per capita (43.96%), and net migration (10.75%); in high-refugee-load countries, they were observed for life expectancy (60.30%), political stability (38.41%), and net migration (16.20%). The framework can support early warning, resilience assessment, and crisis response.

Acknowledgment
We acknowledge with gratitude the financial support provided by the Ministry of Education and Science of Ukraine for the research project “Cybersecurity and digital transformations of the country’s wartime economy: the fight against cybercrime, corruption and the shadow sector,” state registration number 0124U000544.