In the prevailing digital era, heightened by an increasing incidence of cyberattacks, cybersecurity stands out as a critical concern for organizations of all sizes. While the necessity to bolster cybersecurity measures is universally acknowledged, determining an optimal strategy presents a complex challenge. This master thesis introduces a novel approach leveraging inter-company cybersecurity data sharing to assist organizations in honing their defensive measures. A tool was developed to discern the relevance of information-sharing entities by classifying companies across three dimensions: business, economic, and technical. Each dimension is defined by distinct factors, allowing for a precise comparison. An accompanying application was devised to represent the similarities among companies using the Euclidean distance and Pearson correlation. Through extensive evaluation, the Euclidean distance proved superior in the business and economic realms. However, for the technical dimension, dominated by integer values, the efficacy of both measures was comparable, suggesting their combined use for holistic insights. This master thesis offers a strategic pathway for organizations aiming to refine their cybersecurity strategies by leveraging shared data insights
