Defense Advanced Research Projects AgencyTagged Content List

Automation Technologies

Automatic mechanical or digital operation

Showing 60 results for Automation RSS
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.
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.
The Department of Defense’s information technology (IT) infrastructure is made up of a large, complex network of connected local networks comprised of thousands of devices. Cyber defenders must understand and monitor the entire environment to defend it effectively. Toward this end, cyber-defenders work to correlate and understand the information contained in log files, executable files, databases of varying formats, directory structures, communication paths, file and message headers, as well as in the volatile and non-volatile memory of the devices on the network. Meanwhile, adversaries increasingly use targeted attacks that disguise attacks as legitimate actions, making discovery far more difficult. It is within this complicated web of networked systems that cyber defenders must find targeted cyber-attacks.
Existing speech signal processing technologies are inadequate for most noisy or degraded speech signals that are important to military intelligence.
As new defensive technologies make old classes of vulnerability difficult to exploit successfully, adversaries move to new classes of vulnerability. Vulnerabilities based on flawed implementations of algorithms have been popular targets for many years. However, once new defensive technologies make vulnerabilities based on flawed implementations less common and more difficult to exploit, adversaries will turn their attention to vulnerabilities inherent in the algorithms themselves.