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TRACKING
POTENTIAL TERRORISTS
The National Science Foundation recently awarded a $1.8 million grant to Peter Chen, LSU Foundation Murphy J. Foster Professor of computer science, for his research on "cybersecurity" methods that could aid law enforcement and security agencies in tracking and capturing terrorists and other criminals. At the heart of Chen's work is a complex mathematical model and a concept called "smart linkage." Chen explains that "smart linkage" is simply a method of discovering hidden data relationships and building links, based on known or just-discovered relationships between data sets. Some linkages, Chen says, are more important than others. In law enforcement applications, using software and hardware to link existing databases from agencies across the country will allow information to be obtained quickly and easily, he says. Of primary importance in this effort is linking driver's license databases and making it possible to swipe driver's licenses, so valid information and photos of individuals can be accessed by airlines, law enforcement officials, and other officials. Chen points out that most driver's licenses already come with a "swipe" stripe on the back and that driver's license photos and data are already stored electronically by various state agencies. Thus, the primary problem remaining, he says, is to find the most effective and efficient way of connecting, or linking, these databases. The smart linkage technology is only one aspect of Chen's research, however. The complex mathematical model he is devising will help law enforcement and security officials cut down on the labor involved in narrowing lists of suspicious individuals. For instance, he explains, using linked databases, the government or police may come up with a list of thousands of suspicious or "problem" individuals. Then, using a computer program based on the mathematical model, the data on the individuals can be crunched and various factors–location, travel patterns, criminal record, and so forth–used to narrow down the list to perhaps 100 or 1,000, which is much more manageable for investigators. The program is based on a recently developed algorithm for a type of database that Chen created and made famous in the 1970s, called the Entity-Relationship Model. This model "reflects relationships that objects and ideas have in the natural world" and serves as the foundation of many systems analysis and design methodologies, computer-aided software engineering, and repository systems. "Right now, if you go to an airport, everyone is searched indiscriminately. If every passenger is forced to waste one hour, that is huge in terms of time and salary," says Chen. "We could use our resources more efficiently by focusing on the ones who are most likely to be terrorists. Our new algorithm, combined with the Entity-Relationship Model, prioritizes the searches, based on different risks from different people." The methods Chen is researching could also be useful for local law enforcement in situations such as a large-scale hunt for a serial killer. The smart linkage would allow law enforcement agencies from different areas to share information more readily and to narrow the search scope to fit particular profiles or patterns, while possibly avoiding some human errors or preconceptions. ON
THE WEB:
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An
LSU professor could hold the key to successfully tracking or identifying
terrorists, serial killers, and other threats to homeland and
local security.