Cyber-attack Automated Unconventional Sensor Environment (CAUSE)

Past research, such as IARPA’s Open Source Indicators program, shows that combinations of publicly available data sources are useful in the early and accurate detection and forecasting of events, such as disease outbreaks and political crises. In the area of cybersecurity, few have researched methods for a probabilistic warning system that fuses internal sensors (sensors inside the logical boundary of an organization, such as host data) and external sensors (sensors outside the logical and physical boundaries of an organization, such as social media or web search trends).

The CAUSE program seeks multi-disciplinary unconventional sensor technology that will complement existing advanced intrusion detection capabilities. Unconventional sensors will leverage data not typically used in practice today for cybersecurity (at least not in the way the data was originally intended) and may come from non-typical disciplines that can be applied to the cybersecurity domain.

IARPA expects performers to identify and extract novel leading signals from both internal and external sensors (both conventional and unconventional) and use them to generate warnings – probabilistic forecasts and/or detections of cyber-attacks. Performers will generate warnings for real cyber-attacks against one or more U.S. industry organizations that have agreed to participate in CAUSE.

Contracting Office Address:

Office of the Director of National Intelligence
Intelligence Advanced Research Projects Activity
Washington, District of Columbia 20511
United States

For information contact: