Anomaly Detection at Multiple Scales

Anomaly Detection at Multiple Scales
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 government employee [whom] abuses access privileges to share classified information".[2][5] Specific cases mentioned are Nidal Malik Hasan and Wikileaks alleged source Chelsea 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]

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