The largest military conflict in Europe since the Second World War raises natural questions about the economic justification of its causes and its impact on various sectors of the economy. First of all, the defense sector comes under analysis, in which significant changes have taken place in all countries over the last decade. A significant critical review of the literature is carried out in the paper. It revealed how the degree of financing of the defense sector, the transparency of such financing, and its size affect the development of national security and defense resilience, and how deeply these issues were considered from a methodological point of view. The research examines the issue of defense spending in Ukraine, the Russian Federation, the EU, the USA, and China. It is shown that these countries observed different trends in the financing of the army, which was caused by different strategies and approaches to the probability of a high-intensity military conflict. Based on economic and mathematical analysis, the paper demonstrates that the highest level of militarization was observed precisely in the Russian Federation, which was purposefully preparing for war. While Ukraine's military spending was roughly at the same level. The EU and the US had similar dynamics and stable amplitude in military spending. China had a stable percentage of military spending in the state budget. Given the current geopolitical situation, it is supposed to expect further increases in defense expenditures in all of the analysed countries to modernize their armies. The paper emphasizes the importance of transparency and effective budgeting in ensuring a strong and well-equipped army that can defend the country and strengthen its international position. One way to achieve transparency and openness in budgeting is through the development of an appropriate open information system based on the concept of assessing openness and transparency in budgeting and financial management in the defense and security sector of Ukraine, which should be quantitatively measured and programmatically implemented.