Establishment | 2011 |
---|---|
Sponsor | DARPA |
Value | $35 million |
Goal | Detect insider threats in defense and government networks |
Website | www.darpa.mil |
Anomaly Detection at Multiple Scales, or ADAMS, is a $35 million DARPA project designed to identify patterns and anomalies in very large data sets. It is under DARPA's Information Innovation office and began in 2011.[1][2][3][4]
The project is intended to detect and prevent insider threats such as "a soldier in good mental health becoming homicidal or suicidal", an "innocent insider becoming malicious", or a "a government employee [whom] abuses access privileges to share classified information".[2][5] Specific cases mentioned are Nidal Malik Hasan and Wikileaks alleged source Bradley Manning.[6] Commercial applications may include finance.[6] The intended recipients of the system output are operators in the counterintelligence agencies.[2][5]
The Proactive Discovery of Insider Threats Using Graph Analysis and Learning is part of the ADAMS project.[5][7] The Georgia Tech team includes noted high-performance computing researcher David A. Bader.[8]