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

Detection of radioactive material entering national ports: A Bayesian approach to radiation portal data