Sign In

Communications of the ACM

ACM TechNews

Safety in Numbers

View as: Print Mobile App Share:
blast map of Baghdad, Iraq

A new algorithm uses the location of blasts (red) from improvised explosive devices to deduce the hiding places of weapons caches (yellow) in Baghdad, Iraq.

Credit: V.S. Subrahmanian, P. Shakarian, M. Sapino

Mathematicians and computer scientists are working on equations and algorithms that exhibit potential as terrorism countermeasures. Among such advances are powerful new algorithms that mine vast volumes of data and extract hidden rules that govern terrorism behavior. By simulating the internal tensions between secrecy and the need to communicate, researchers can anticipate terror cells' organizational patterns.

A network arrangement known as fuzzy group clustering locates people who belong to two distinct groups at the same time, and models suggest that such "interstitial" members probably are key coordinators of a terrorist operation. University of Maryland professor V.S. Subrahmanian and colleagues are testing an algorithm that identifies and extracts terrorist-associated keywords from news databases, with the goal of having the program ultimately extract more than 700 factors accurately and automatically.

Meanwhile, Tilburg University's Roy Lindelauf and colleagues have devised a description of a resilient cell using cooperative game theory. The researchers discovered that the ideal organizational structure shifts as the threat of being discovered rises, allowing them to "predict structures that resemble organization structures that we observe in reality," according to Lindelauf.

From Science News
View Full Article


Abstracts Copyright © 2010 Information Inc., Bethesda, Maryland, USA


No entries found