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RESUMO Digital data production increases on a daily basis due to the widespread use of Internet and interconnected computing devices. Acting security mechanisms may result in several types of information, if processed and correlated, since their output logs range from IP addresses/regions to attack events. Hence, the application of data science techniques is essential to extract knowledge and insights from this massive amount of data. In this article, we present a platform for cybersecurity data visualization in an effort to identify trends, associations and patterns, which enable better data-driven decisions. To prototype and test the proposed platform, we focused on endpoint logs provided from a cybersecurity company. The conclusions drawn from this study are that there is a substantial concentration of victims in urbanized areas, notably the state capitals, as well as a higher risk level for Server Operating Systems. Nevertheless, these results are still preliminary, considering the limitations of the dataset (few, specific samples from internal testing endpoints), but helped pave the way towards new models for further threat analysis.

Uma Plataforma para Correlação, Visualização e Extração de Tendências de Dados de Segurança