Open AccessBiometric‐enabled watchlists technology
Author(s) -
Lai Kenneth,
Kanich Ondřej,
Dvořák Michal,
Drahanský Martin,
Yanushkevich Svetlana,
Shmerko Vlad
Publication year - 2018
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
ISSN - 2047-4946
DOI - 10.1049/iet-bmt.2017.0036
Subject(s) - biometrics , computer science , quality (philosophy) , identification (biology) , metric (unit) , fingerprint (computing) , data science , computer security , philosophy , operations management , botany , epistemology , economics , biology
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.