Using burst detection techniques to identify suspicious vehicular traffic at border crossings
Siddharth Kaza, Hsin‐Min Lu, Daniel Dajun Zeng, Hsinchun Chen · 2012
Border safety is a critical part of national and international security. The Department of Homeland Security (DHS) searches vehicles entering the country at land borders for drugs and other contraband. However, this process is time-consuming and operational efficiency is needed for smooth operations at the border. To aid in the screening of vehicles, we propose to examine traffic patterns at checkpoints using burst detection algorithms. Our results show that the overall traffic at the border shows bursting patterns attributable to week days and the holiday seasons. In addition, using local law-enforcement data we also find that traffic with prior contacts with law-enforcement shows a bursting pattern distinct from other traffic. We also find that such bursts in suspicious traffic can be attributable to increases in vehicular traffic associated with certain kinds of criminal activity. This information can be used to specifically target vehicles searches during primary screening at ports and in the surrounding areas.