Challenges to national defence in contemporary geopolitical situation

This study examines the reliability of financial reporting in the Russian defence industry amidst the ongoing conflict in Ukraine and the resulting Western sanctions. Using Benford’s Law, the authors analyse accounting data (Total Assets, Turnover, and Profit/Loss) from selected strategic sectors (NACE 2540, 3030, and 3040) between 2015 and 2024. The results reveal a significant and growing deviation from the theoretical distribution of leading digits, particularly following the 2022 invasion. Specific anomalies—such as the anomalous excess of the digit 1 in Total Assets and the concentration of digits 2 and 9 in Profit/Loss—point to systematic asset padding, creative margin management, and the use of accounting as a tool for strategic disinformation. The analysis suggests that while Russian authorities attempt to maintain a facade of economic stability through “controlled fiction”, statistical testing uncovers underlying institutional stress, asset degradation, and the shift towards a closed-loop war economy. The study concludes that Benford’s Law is a vital tool for detecting operational paralysis and information manipulation when primary data are classified or unreliable.

The article analyzes the healthcare sector as a strategic target in hybrid conflicts, with a focus on cyber threats. Based on OSINT and a comparative analysis of incidents, it identifies typical attack patterns, their operational impacts, and systemic vulnerabilities in healthcare systems. The findings demonstrate that cyber incidents disrupt healthcare delivery and have broader security implications. The study emphasizes the need to integrate cybersecurity, crisis management, and the protection of sensitive patient data.

This paper analyzes the resilience of healthcare systems in the context of armed conflicts and hybrid threats, focusing on the role of healthcare data and process management. Based on a mixed-methods approach combining qualitative and quantitative research, it identifies key systemic vulnerabilities, particularly in the areas of data sharing and coordination. The results highlight the need for healthcare organizations to prepare for operations in the event of digital infrastructure disruptions and emphasize the importance of the ability to transition to alternative modes of operation as a key element of resilience.

This article addresses the reassessment of security threats to the Czech Republic in light of developments in the security environment since 2015. The aim is to update the evaluation of selected types of threats and to reflect their current characteristics, with particular emphasis on their interdependencies and their capacity to generate cascading effects. To achieve this objective, a semi-quantitative risk assessment model is applied and extended by incorporating a cascading effect coefficient. The results of the risk assessment indicate that cyberattacks, pandemics, floods, and hazardous substance releases constitute unacceptable risks, whereas the remaining assessed threats fall within the category of conditionally acceptable risks. The proposed methodological extension enables a more accurate assessment of interconnected threats. The findings may be applied in risk assessment processes within crisis management.

The aim of this article is to analyse the approaches to population sheltering in Switzerland, Finland, and Sweden. The research methodology is based on a previously published article by the authors [1], in which the relative criteria of approaches to population sheltering in selected countries were identified and evaluated using Saaty method and the weighted sum method. This procedure is now also applied to the newly assessed countries. The analysis of sheltering in Switzerland, Finland, and Sweden highlighted common features resulting from the inclusion of sheltering within the system of total national defence, as well as differences in the systemic integration of sheltering among the countries under review. The findings suggest that an effective sheltering system is contingent upon sustained political support, a clear legislative framework, and the integration of protective infrastructure into the broader framework of national security.

This article focuses on modeling the spread of disinformation narratives on social media using the SEDPNR epidemiological model, an extension of the basic SEIR model that takes into account the specifics of digital communication. This includes the existence of a "doubt" phase and the division of active users according to their sentiment polarity. The analyzed data describe a specific disinformation narrative, “Biolabs Ukraine,” that spread in connection with the Russian invasion of Ukraine. The results demonstrate that the dissemination of the narrative exhibits characteristics of an infodemic wave: a rapid increase, a brief peak, and a subsequent decline. The analysis confirms the significant role of active users and shows that supportive and critical reactions both contribute to the further dissemination of content.