Information Innovation Office (I2O)

Embedded systems form a ubiquitous, networked, computing substrate that underlies much of modern technological society. Such systems range from large supervisory control and data acquisition (SCADA) systems that manage physical infrastructure to medical devices such as pacemakers and insulin pumps, to computer peripherals such as printers and routers, to communication devices such as cell phones and radios, to vehicles such as airplanes and satellites. Such devices have been networked for a variety of reasons, including the ability to conveniently access diagnostic information, perform software updates, provide innovative features, lower costs, and improve ease of use. More

Military intelligence analysts face the monumental and escalating task of analyzing massive volumes of complex data from multiple, diverse sources such as physical sensors, human contacts and contextual databases. These analysts consume and process information from all available sources to provide mission-relevant, timely insights to commanders. To enhance this largely manual process, analysts require more effective and efficient means to receive, correlate, analyze, report and share intelligence. More

In supervised machine learning (ML), the ML system learns by example to recognize things, such as objects in images or speech. Humans provide these examples to ML systems during their training in the form of labeled data. With enough labeled data, we can generally build accurate pattern recognition models. More

LADS will develop a new protection paradigm that separates security-monitoring functionality from the protected system, focusing on low-resource, embedded and Internet of Things (IoT) devices. The program will explore technologies to associate the running state of a device with its involuntary analog emissions across different physical modalities including, but not limited to, electromagnetic emissions, acoustic emanations, power fluctuations and thermal output variations. More

The U.S. Government operates globally and frequently encounters so-called “low-resource” languages for which no automated human language technology capability exists. Historically, development of technology for automated exploitation of foreign language materials has required protracted effort and a large data investment. Current methods can require multiple years and tens of millions of dollars per language—mostly to construct translated or transcribed corpora. More