|photo credit: wired.com|
The military is scrambling to identify disgruntled or radicalized troops who pose a threat to themselves or their buddies. So the futurists at Darpa are asking for algorithms to find and pre-empt anyone planning the next Fort Hood massacre, WikiLeaks document dump or suicide-in-uniform.
This counterintelligence-heavy effort isn’t Darpa’s typical push to create flying Humvees or brainwave-powered prosthetic limbs. But the Pentagon’s far-out R&D team has made other moves recently to hunt down threats from within.
The idea behind the Anomaly Detection at Multiple Scales, or Adams, effort is to sift through “massive data sets” to find the warning signs of looming homicide, suicide or other destructive behavior. “The focus is on malevolent insiders that started out as ‘good guys.’ The specific goal of Adams is to detect anomalous behaviors before or shortly after they turn,” the agency writes in its program announcement.
Currently, Darpa says, the Defense Department doesn’t actually know how “a soldier in good mental health” actually comes to pose an “insider threat,” defined as “an already trusted person in a secure environment with access to sensitive information and information systems and sources.” (WikiLeaks, anyone?)
“When we look through the evidence after the fact, we often find a trail –- sometimes even an ‘obvious’ one,” Darpa adds. “The question is can we pick up the trail before the fact, giving us time to intervene and prevent an incident? Why is that so hard?”
Adams is supposed to fill the breach. But what kind of tech would be necessary to detect these anomalies?
What sort of data actually represent worrisome anomalies, as opposed to a soldier harmlessly venting steam?
(Click here to read the full story on the Wired.com website.)