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Understanding the properties exhibited by Spatial-temporal evolution of cyberattacks improve cyber threat intelligence. In addition, better understanding onthreats patterns is a key feature for cyber threats prevention, detection, andmanagement and for enhancing defenses. In this work, we study different aspectsof emerging threats in the wild shared by 160,000 global participants form allindustries. First, we perform an exploratory data analysis of the collectedcyber threats. We investigate the most targeted countries, most common malwaresand the distribution of attacks frequency by localisation. Second, we extractattacks' spreading patterns at country level. We model these behaviors usingtransition graphs decorated with probabilities of switching from a country toanother. Finally, we analyse the extent to which cyber threats have beenaffected by the COVID-19 outbreak and sanitary measures imposed by governmentsto prevent the virus from spreading.

Leveraging Open Threat Exchange (OTX) to Understand Spatio-Temporal Trends of Cyber Threats: Covid-19 Case Study