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Combating Nuclear Smuggling

Exploring the development and deployment of nuclear detection systems for border monitoring

Sensitive nuclear and radiological materials have been stolen and trafficked by criminal groups and individuals across national borders. In response, countries have developed radiation detection systems aimed at identifying undeclared nuclear and radiological materials while in transit.

CSSS staff have explored how and for what purpose detection systems are ultimately implemented, with a focus on maritime facilities. Authoring a state of play study, funded by the Cabinet Office and presented at Wilton Park in the run up to the 2016 Nuclear Security Summit. Observations and recommendations from this study fed into the UK-US Joint Statement on Maritime Supply Chain Security presented at the Summit together with an accompanying Best Practice Guide. A more detailed exploration of the different drivers that inform the practical implementation of detection systems can be found in Dr Robert J. Downes, Professor Christopher Hobbs and Dr Daniel Salisbury's 2019 article, 'Combating nuclear smuggling?', in the Non-Proliferation Review. This article identifies a currently fragmented global nuclear detection architecture, where there exists considerable scope for the development new standards and guidance, the increased sharing of best practice and new tools to support key part of the detection process.

The maritime supply chain is a complex environment within which to operate radiation detection systems. This is due in part to the presence of large quantities of Naturally Occurring Radioactive Materials (NORM) and commercial radioactive shipments, which can mask the signature of key threat materials. Under Coordinated Research Project funded by the International Atomic Energy Agency (IAEA) CSSS staff have partnered with the Department of Informatics at KCL to explore how data science techniques might improve the assessment of alarm from Radiation Portal Monitors. In Prof Christopher Hobbs, Prof Peter McBurney, and Dominic Oliver's 2020 article, 'Data Science in Support of Radiation Detection for Border Monitoring', published in Science and Global Security, the authors explore how the use of Dynamic Time Warping and Agglomerative Hierarchal Clustering can improve the ability of radiation portal monitors to characterize alarm.


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