This paper addresses the facial biometric-enabled watchlist technology in which risk detectors are mandatory mechanisms for early detection of threats, as well as for avoiding offense to innocent travelers. We propose a multiparametric cost assessment and relative entropy measures as risk detectors. We experimentally demonstrate the effects of mis-identification and impersonation under various watchlist screening scenarios and constraints. The key contributions of this paper are the novel techniques for design and analysis of the biometric-enabled watchlist and the supporting infrastructure, as well as measuring the impersonation impact on e-border performance.
@article{arxiv.2007.11328,
title = {Watchlist Risk Assessment using Multiparametric Cost and Relative Entropy},
author = {K. Lai and S. N. Yanushkevich},
journal= {arXiv preprint arXiv:2007.11328},
year = {2020}
}