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.