access icon free Biometric-enabled watchlists technology

For Entry-Exit technologies, such as US VISIT and Smart Borders (e-borders), a watchlist normally contains high-quality biometric traits and is checked only against visitors. The situation can change drastically if low-quality images are added into the watchlist. Motivated by this fact, we introduce a systematic approach to assessing the risk of travellers using a biometric-enabled watchlist where some latency of the biometric traits is allowed. The main results presented herein include: (1) a taxonomical view of the watchlist technology, and (2) a novel risk assessment technique. For modelling the watchlist landscape, we propose a risk categorisation using the Doddington metric. We evaluate via experimental study on large-scale facial and fingerprint databases, the risks of impersonation and mis-identification in various screening scenarios. Other contributions include a study of approaches to designing a biometric-enabled watchlist for e-borders: a) risk control and b) improving performance of the e-border via integrating the interview supporting machines.

Inspec keywords: risk management; biometrics (access control); fingerprint identification; face recognition

Other keywords: risk categorisation; Doddington metric; e-borders; risk assessment technique; watchlist landscape modelling; large-scale facial databases; systematic approach; high-quality biometric traits; fingerprint databases; entry-exit technologies; biometric-enabled watchlists technology; risk control

Subjects: Image recognition; Data security; Computer vision and image processing techniques

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