Defense Advanced Research Projects AgencyTagged Content List

Data Analysis at Massive Scales

Extracting information and insights from massive datasets; "big data"; "data mining"

Showing 43 results for Data + Programs RSS
Networks within the United States and abroad face increasingly broad-spectrum cyber threats from numerous actors and novel attack vectors. Malicious activity also crosscuts organizational boundaries, as nefarious actors use networks with less protection to pivot into networks containing key assets. Detection of these threats requires adjustments to network and host sensors at machine speed. Additionally, the data required to detect these threats may be distributed across devices and networks. In all of these cases, the threat actors are using technology to perpetrate their attacks and hide their activities and movement, both physical and virtual, inside DoD, commercial, and Internet Access Provider (IAP) networks.
Understanding the complex and increasingly data-intensive world around us relies on the construction of robust empirical models, i.e., representations of real, complex systems that enable decision makers to predict behaviors and answer “what-if” questions. Today, construction of complex empirical models is largely a manual process requiring a team of subject matter experts and data scientists.
Department of Defense (DoD) operators and analysts collect and process copious amounts of data from a wide range of sources to create and assess plans and execute missions. However, depending on context, much of the information that could support DoD missions may be implicit rather than explicitly expressed. Having the capability to automatically extract operationally relevant information that is only referenced indirectly would greatly assist analysts in efficiently processing data.
Deep Purple aims to advance the modeling of complex dynamic systems using new information-efficient approaches that make optimal use of data and known physics at multiple scales. The program is investigating next-generation deep learning approaches that use not only high throughput multimodal scientific data from observations and controlled experiments (including behaviors such as phase transitions and chaos), but also of the known science of such systems at whatever scales it exists.
As a result of combat exposure, warfighters may return home from deployments with psychological health challenges and find it difficult to reconnect with family and society at large. According to the Department of Veteran Affairs’ National Center for PTSD, studies show that between 12 and 25 percent of military personnel who had returned from Afghanistan and Iraq as of 2008 may suffer from PTSD. (1) Despite best efforts to improve awareness and care, additional studies reveal that only a small fraction of warfighters seek help dealing with psychological health issues.