Social Cyber Security

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Social Cyber Security is an emerging scientific area focused on the science to characterize, understand, and forecast changes in human behavior, social, cultural and political outcomes, and to build the cyber-infrastructure needed for society to persist in its essential character in a cyber mediated information environment under changing conditions and actual or imminent cyber threats.

We explore who promotes attacks, who is threatened, what conditions increase the likelihood of attack, and how to respond to or mitigate the impact of attacks. Our approach is multi-methodological using network analysis, social science theories, visualization, machine learning, text mining, social media analytics and spatio-temporal data mining. The data being used is large scale digital data including, but not limited to, social media, electronic records, and netflow data. The data being analyzed are massive, but also typically represent only a biased sample, often composed of ephemeral, time variant, and the raw data is always non-sharable data.

The rapid rate of change in cyber-technologies, evolving legal and policy constraints, and rapid rate at which information can flow globally are creating an environment where science needs to be done at scale and very rapidly. This often entails the need for advanced cyberinfrastructure, including edge, cloud, and high performance computing.

Keeping these considerations in mind, our three main foci at the moment: social media and cyber attacks, cyber team training, and threat prediction. There are some factors that inter-relate these foci; e.g. twitter data is used in both the social media and the threat prediction area; and the cyber team training is designed to teach cyber teams how to respond to the types of threats discovered under threat predict.

Social Media and Cyber Security Team (supported by ONR)

  • Sumeet Kumar - CASOS Center
  • Ghita Mezzour - Collaborator, University of Rabat
  • Huan Liu - Collaborator, Arizona State University

Cyber Training (supported by ONR and SEI)

  • Geoffrey Dobson - CASOS Center, SEI
  • Done with Collaboration with the Software Engineering Institute (SEI)

Threat Prediction Team (supported by ONR, SEI, City of Pittsburgh and NATO)

  • Adam Tse - CASOS Center, SEI
  • Ghita Mezzour - Collaborator, University of Rabat
  • Jerome Francois - Collaborator, INRIA
  • Abdelkader Lahmadi - Collaborator

Additional information about this project can be found at the INRIA website, http://threatpredict.inria.fr/.