This article explores the role of correlation analysis of standardized types of cyber incidents within the context of information technology for securing international communications. The study applies correlation analysis to various types of anonymized cyber incidents in Ukraine to identify relationships between them, across established categories and types, from June 2022 to February 2024. A heatmap of correlations is used to visualize the results and further analyze the patterns in the dynamics of threats. Particular attention is paid to the possibility of using heatmaps to visually represent correlations between different types of cyber incidents. This approach allows for effective analysis of large data volumes and the identification of complex relationships that may be obscure in traditional analysis. The article focuses on the methodology of processing incident data using statistical methods to assess relationships. Correlation analysis is performed using the Pearson correlation coefficient, and the results are presented in the form of heatmaps, which allow identifying both strong and weak correlations between incident categories. This approach reveals multifactorial cyber t
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