Automated Detection of Anomalous Shipping Manifests to Identify Illicit Trade

Conference · Tue Nov 12 00:00:00 EST 2013

DOI:https://doi.org/10.1109/THS.2013.6699059· OSTI ID:1117085

Sanfilippo, Antonio P.; Chikkagoudar, Satish

We describe an approach to analyzing trade data which uses clustering to detect similarities across shipping manifest records, classification to evaluate clustering results and categorize new unseen shipping data records, and visual analytics to provide to support situation awareness in dynamic decision making to monitor and warn against the movement of radiological threat materials through search, analysis and forecasting capabilities. The evaluation of clustering results through classification and systematic inspection of the clusters show the clusters have strong semantic cohesion and offer novel ways to detect transactions related to nuclear smuggling.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1117085
• Report Number(s): PNNL-SA-94488
• Resource Relation: Conference: IEEE Conference on Technologies for Homeland Security (HST 2013), November 12-14, 2013, Waltham, MA, 529-534
• Country of Publication: United States
• Language: English

Related Subjects

trade data
clustering
classification
visual analytics
illicit trafficking
detection of radiological threat materials
nuclear smuggling