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DARPA’s investment strategy begins with a portfolio approach. Reaching for outsized impact means taking on risk, and high risk in pursuit of high payoff is a hallmark of DARPA’s programs. We pursue our objectives through hundreds of programs. By design, programs are finite in duration while creating lasting revolutionary change. They address a wide range of technology opportunities and national security challenges. This assures that while individual efforts might fail—a natural consequence of taking on risk—the total portfolio delivers. More

For reference, past DARPA research programs can be viewed in the Past Programs Archive.

Embedded computing systems are ubiquitous in critical infrastructure, vehicles, smart devices, and military systems. Conventional wisdom once held that cyberattacks against embedded systems were not a concern since they seldom had traditional networking connections on which an attack could occur. However, attackers have learned to bridge air gaps that surround the most sensitive embedded systems, and network connectivity is now being extended to even the most remote of embedded systems. More
| Cyber | Formal | Trust |
The rapid pace of innovation in software and hardware over the past three decades has produced computational systems that, despite security improvements, remain stubbornly vulnerable to attack. Although clean-sheet design can produce fundamental security improvements that gradually diffuse into the installed base, this process can take years. More
DARPA’s Cyber Grand Challenge is a first-of-its-kind tournament designed to speed the development of automated security systems able to defend against cyberattacks as fast as they are launched. More
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. More
High performance optoelectronic systems, e.g. ultra low-noise lasers and optoelectronic signal sources, are employed in numerous applications such as fiber optic communications, high-precision timing references, LADAR, imaging arrays, etc. Current state-of-the-art ultra-low noise lasers and optoelectronic signal sources use macro-scale photonics for mechanical and thermal noise suppression, and off-chip electronics for feedback control. The benchtop or rack mount component-level assembly of these sources limits photonic coupling efficiency as well as the speed of electronic feedback, and also adds size and weight to the system. Integration of these components in a chip-scale form factor could greatly mitigate these limitations. More
The DAHI Foundry Technology program thrust seeks to establish an accessible, manufacturable technology for device-level heterogeneous integration of a wide array of materials and devices (including, for example, multiple electronics and MEMS technologies) with complex silicon-enabled (e.g. CMOS) architectures on a common silicon substrate. of The DAHI Foundry Technology thrust will incorporate and build upon the heterogeneous integration technologies of the COSMOS and E-PHI program thrusts, while also developing new capabilities in heterogeneous integration processes, yield and circuit design innovation.  More
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. More
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. More