Last autumn Lawrence Wein detected a serious problem in the U.S. government's US-VISIT program, designed to capture terrorists entering American airports by checking their fingerprints. The Stanford Graduate School of Business faculty member presented his findings to the White House and the U.S. Department of Homeland Security and testified before two subcommittees of the U.S. House of Representatives Select Committee on Homeland Security. Wein's work sounded alarm bells among politicians and government officials and prompted the government to revisit the design and implementation of the US-VISIT program. His findings are being released this week in an academic journal.
As a result of the September 11, 2001, attacks on the World Trade Center and the Pentagon, most foreign citizens entering the United States have been required to have their fingerprints checked against those of known terrorists. Under the US-VISIT program now in effect, U.S. Customs officials at airports lay each foreign visitor's two index fingers down on a special pad and then wait while the computer compares the images against the fingerprints stored in the system of several million known criminals and suspected terrorists. When the computer detects a match, a person is quietly sequestered for further investigation. While the system is 96 percent accurate overall, Wein has found that its performance degrades when fingerprint quality is not good.
Using mathematical models, Wein, along with Manas Baveja, a Ph.D. student at Stanford's Institute for Computational and Mathematical Engineering and a science fellow at the university's Center for International Security and Cooperation, has specifically determined that when image quality is poor, accuracy drops to 53 percent. "About 5 percent of the general public and 10 percent of those on the watch list have bad quality fingerprints due either to genetics or hard labor," Wein says. It's those small percentages that can evade the system -- with potentially huge consequences. "We assume that terrorist organizations will eventually defeat the US-VISIT program by employing a majority of people whose fingerprint quality is either naturally bad or deliberately made so," he says.
Wein and Baveja developed various mathematical models that calculated how the system could be tweaked to improve accuracy while not increasing either visitor waiting times at airports or the need for more customs staffing. "We found that instead of scanning two index fingers, scanning eight to ten fingers will result in a 95 percent detection probability, even when fingerprint quality is bad," Wein says.
In the meantime, Wein has proposed a shorter-term solution that will require only a minor software modification. "By loosening the detection thresholds on poor images you can catch more of these people," he says. "You make up for the additional secondary inspection time this takes by slightly raising detection thresholds on good images." Such an adjustment should raise the likelihood of catching suspects with the worst quality images from 53 to 73 percent.
Wein, the Paul E. Holden Professor of Management Science at the Stanford Graduate School of Business, details his research in an article titled "Using Fingerprint Image Quality to Improve the Identification Performance of the U.S. Visitor and Immigrant Status Indicator Technology Program," co-authored with Manas Baveja. The paper appears in the May 9-13 issue of the Proceedings of the National Academy of Sciences. http://www.pnas.org/papbyrecent.shtml