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

By Georgia Tech News

November 16, 2011

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Researchers at the U.S. Defense Advanced Research Projects Agency (DARPA), the Army Research Office, and Georgia Tech are developing new approaches for identifying insider threats before a data breach occurs.

The researchers are developing a suite of algorithms that can detect different types of insider threats by analyzing massive amounts of data for unusual activity. "Our goal is to develop a system that will provide analysts for the first time a very short, ranked list of unexplained events that should be further investigated," says Georgia Tech professor David A. Bader.

The researchers also are developing a prototype Anomaly Detection at Multiple Scales (ADAMS) system, which they say could revolutionize the capabilities of counterintelligence professions by prioritizing potential malicious insider threats against a background of normal network activity.

The ADAMS system will analyze terabytes of data using new algorithms to quickly find anomalies. "We need to bring together high-performance computing, algorithms, and systems on an unprecedented scale because we're collecting a massive amount of information in real time for a long period of time," Bader says.

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