Washington, February 27 : An Indian origin researcher at the University of Maryland's Institute of Advanced Computer Studies (UMIACS) has unveiled software that may facilitate faster analysis and forecasting of terrorism.
V.S. Subrahmanian, a computer science professor who heads that project, calls the new program the SOMA Terror Organization Portal (STOP).
He says that the new program will allow analysts to query automatically learnt rules on terrorist organization behaviour, forecast potential behaviour based on such rules, and, most importantly, to network with other analysts examining the same subjects.
SOMA (Stochastic Opponent Modeling Agents) is a formal, logical-statistical reasoning framework that uses data about past behaviour of terror groups in order to learn rules about the probability of an organization, community, or person taking certain actions in different situations.
In collaboration with computer scientists and political scientists, SOMA has generated tens of thousands of rules about the likely behaviour of each of about 30 groups, which include Hezbollah, Hamas, and Hezb-I-Islami.
"SOMA is a significant joint computer science and social science achievement that will facilitate learning about and forecasting terrorist group behaviour based on rigorous mathematical and computational models," said Subrahmanian.
"But even the best science needs to work hand in hand with social scientists and users. In addition to accurate behavioural models and forecasting algorithms, the SOMA Terror Organization Portal acts as a virtual roundtable that terrorism experts can gather around and form a rich community that transcends artificial boundaries," he added.
So far, the SOMA Terror Organization Portal has users from four defence agencies.
Besides performing queries and running a prediction engine, the users can also mark rules as useful or not useful, and leave comments about the rules. This feature of the program will enable them to learn what others have found useful, and to identify interesting rules and comments.
"Security analysts need more than piles of data. It takes a network to fight a network. Analysts need to learn from other analysts. This system allows multiple users to arrive at a shared understanding of how a terror group operates and what it might do in the future. Using the queries analysts can examine the underlying data and then, using the forecasting capabilities, test their theories," says UMIACS researcher Aaron Mannes.
The project was funded by the Air Force Office of Scientific Research.