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September 2010 Detection of radioactive material entering national ports: A Bayesian approach to radiation portal data
Siddhartha R. Dalal, Bing Han
Ann. Appl. Stat. 4(3): 1256-1271 (September 2010). DOI: 10.1214/10-AOAS334

Abstract

Given the potential for illicit nuclear material being used for terrorism, most ports now inspect a large number of goods entering national borders for radioactive cargo. The U.S. Department of Homeland Security is moving toward one hundred percent inspection of all containers entering the U.S. at various ports of entry for nuclear material. We propose a Bayesian classification approach for the real-time data collected by the inline Polyvinyl Toluene radiation portal monitors. We study the computational and asymptotic properties of the proposed method and demonstrate its efficacy in simulations. Given data available to the authorities, it should be feasible to implement this approach in practice.

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Siddhartha R. Dalal. Bing Han. "Detection of radioactive material entering national ports: A Bayesian approach to radiation portal data." Ann. Appl. Stat. 4 (3) 1256 - 1271, September 2010. https://doi.org/10.1214/10-AOAS334

Information

Published: September 2010
First available in Project Euclid: 18 October 2010

zbMATH: 1202.62184
MathSciNet: MR2758327
Digital Object Identifier: 10.1214/10-AOAS334

Keywords: Bayesian classifier , machine learning , nuclear detection , Poisson model , terrorism

Rights: Copyright © 2010 Institute of Mathematical Statistics

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Vol.4 • No. 3 • September 2010
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