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YANUSHKEVICH, S. EASTWOOD, S. DRAHANSKÝ, M. SHMERKO, V.
Original Title
Understanding and taxonomy of uncertainty in modeling, simulation, and risk profiling for border control automation
Type
journal article in Web of Science
Language
English
Original Abstract
This paper addresses the problem of trust in Modeling and Simulation (M&S) technologies, and uncertainty in applications to homeland security. The key goal of this paper is an extension of the notion of trusted M&S techniques for traveler risk assessment in mass-transit applications such as e-borders. Theories of uncertainty suggest that different understandings of uncertainty result in different mechanisms of its reduction. We show that a taxonomy of uncertainty that is accepted in philosophical studies, as well as the NATO methodology of uncertainty assessment (known as the Admiralty Code), can be useful in M&S. This paper overviews various approaches to M&S and focuses on a framework that is based on multi-source fusion mechanisms using Dempster Shafer (DS) theory. The DS metric is useful for the development of simulators, recommender machines, and risk profilers when expert knowledge is given in an imprecise form. The difference between the Bayesian and DS metrics is introduced via a demonstrative experiment from the area of traveler risk assessment using a biometric-enabled watchlist.
Keywords
Uncertainty taxonomy, Admiralty Code, automated border control, Bayesian network, watchlist technology, Dempster-Shafer metric
Authors
YANUSHKEVICH, S.; EASTWOOD, S.; DRAHANSKÝ, M.; SHMERKO, V.
Released
30. 7. 2016
ISBN
1548-5129
Periodical
Journal of Defense Modeling and Simulation
Year of study
15
Number
1
State
United States of America
Pages from
95
Pages to
109
Pages count
URL
http://dms.sagepub.com/content/early/2016/07/28/1548512916660637.full.pdf?ijkey=R9SCdz5xzrtfIce&keytype=finite
BibTex
@article{BUT130916, author="Svetlana {Yanushkevich} and Shawn {Eastwood} and Martin {Drahanský} and Vlad. {Shmerko}", title="Understanding and taxonomy of uncertainty in modeling, simulation, and risk profiling for border control automation", journal="Journal of Defense Modeling and Simulation", year="2016", volume="15", number="1", pages="95--109", doi="10.1177/1548512916660637", issn="1548-5129", url="http://dms.sagepub.com/content/early/2016/07/28/1548512916660637.full.pdf?ijkey=R9SCdz5xzrtfIce&keytype=finite" }