Using fingerprint image quality to improve the identification performance of the U.S. Visitor and Immigrant Status Indicator Technology Program

摘要

Motivated by the difficulty of biometric systems to correctly match fingerprints with poor image quality, we formulate and solve a game-theoretic formulation of the identification problem in two settings: U.S. visa applicants are checked against a list of visa holders to detect visa fraud, and visitors entering the U.S. are checked against a watchlist of criminals and suspected terrorists. For three types of biometric strategies, we solve the game in which the U.S. Government chooses the strategy's optimal parameter values to maximize the detection probability subject to a constraint on the mean biometric processing time per legal visitor, and then the terrorist chooses the image quality to minimize the detection probability. At current inspector staffing levels at ports of entry, our model predicts that a quality-dependent two-finger strategy achieves a detection probability of 0.733, compared to 0.526 under the quality-independent two-finger strategy that is currently implemented at the U.S. border. Increasing the staffing level of inspectors offers only minor increases in the detection probability for these two strategies. Using more than two fingers to match visitors with poor image quality allows a detection probability of 0.949 under current staffing levels, but may require major changes to the current U.S. biometric program. The detection probabilities during visa application are ≈11–22% smaller than at ports of entry for all three strategies, but the same qualitative conclusions hold.