Anomaly Detection at Multiple Scales

Georgia Tech Helps to Develop System That Will Detect Insider Threats from Massive Data Sets

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Researchers from Georgia Tech are helping to create a suite of algorithms that can detect multiple types of insider threats by analyzing massive amounts of data for unusual activity. The Georgia Tech research team includes (left-right) Erica Briscoe, Andy Register, David A. Bader, Richard Boyd, Anita Zakrzewska, Oded Green, Lora Weiss, Edmond Chow and Oguz Kaya. (Credit: Gary Meek)

When a soldier in good mental health becomes homicidal or a government employee abuses access privileges to share classified information, we often wonder why no one saw it coming. When looking through the evidence after the fact, a trail often exists that, had it been noticed, could have possibly provided enough time to intervene and prevent an incident.

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