Georgia Tech researchers, in collaboration with researchers at Oregon State University, the University of Massachusetts, and Carnegie Mellon University, are developing the Proactive Discovery of Insider Threats Using Graph Analysis and Learning (PRODIGAL) system.
PRODIGAL is designed to scan up to 250 million text messages, emails, and file transfers to identify insider threats or employees that are about to turn against the organization. The system will integrate graph processing, anomaly detection, and relational machine learning to create a prototype Anomaly Detection at Multiple Scales system.
PRODIGAL, which initially would be used to monitor the communications in civilian, government, and military organizations in which employees have agreed to be monitored, is intended to identify rogue individuals, according to the researchers.
"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 Bader.
From Government Computer News
View Full Article
Abstracts Copyright © 2011 Information Inc. , Bethesda, Maryland, USA
No entries found