In a nutshell, the project aims at characterizing the relationships between security events and social and geographical related data and, using this knowledge, to finally predict future cybersecurity threats and attacks that will occur. We especially aim to improve the research community’s understanding of cyber security as a socio-technical problem by analysing and describing large datasets from multiple sources.
This project proposes a disruptive methodology for cyber-threat intelligence by improving our understanding of the effect of global societal events on cyber security. Currently, we know of many geo-political, sport, entertainment events that had a direct effect on cyber security. That knowledge is, however, mostly anecdotal. This project will help systematize that knowledge.
To realize this objective, the project contribution is three-fold:
- Collection, storage and clustering of both technical and social data within a shared and safe repository
- Correlation of societal and technical data (security related) to highlight their inter-dependency
- Prediction of security threats