Using burst detection techniques to identify suspicious vehicular traffic at border crossings

Siddharth Kaza, Hsin Min Lu, Dajun Zeng, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics: Cyberspace, Border, and Immigration Securities
Pages212-214
Number of pages3
DOIs
Publication statusPublished - 2012
Event2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012 - Washington, DC, United States
Duration: Jun 11 2012Jun 14 2012

Other

Other2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012
CountryUnited States
CityWashington, DC
Period6/11/126/14/12

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Keywords

  • border crime
  • border crossing traffic
  • burst detection
  • primary screening

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Kaza, S., Lu, H. M., Zeng, D., & Chen, H. (2012). Using burst detection techniques to identify suspicious vehicular traffic at border crossings. In ISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics: Cyberspace, Border, and Immigration Securities (pp. 212-214). [6284311] https://doi.org/10.1109/ISI.2012.6284311