Target vehicle identification for border safety with modified mutual information

Siddharth Kaza, Yuan Wang, Hsinchun Chen

Research output: Contribution to conferencePaperpeer-review

Abstract

In recent years border security has been identified as a critical part of homeland security. The Department of Homeland Security monitors vehicles entering and leaving the country at land borders. Some vehicles are targeted to search for drugs and other contraband. Customs and Border Protection agents believe that vehicles involved in illegal activity operate in groups. If the criminal links of one vehicle are known then their border crossing patterns can be used to identify other partner vehicles. We perform this association analysis by using mutual information (MI) to identify pairs of vehicles that are potentially involved in criminal activity. Domain experts also suggest that criminal vehicles may cross at certain times of the day to evade inspection. We propose to modify the MI formulation to include this heuristic by using cross-jurisdictional criminal data from border-area jurisdictions.

Original languageEnglish (US)
Pages410-411
Number of pages2
DOIs
StatePublished - Dec 1 2006
Event7th Annual International Conference on Digital Government Research, Dg.o 2006 - San Diego, CA, United States
Duration: May 21 2006May 24 2006

Other

Other7th Annual International Conference on Digital Government Research, Dg.o 2006
CountryUnited States
CitySan Diego, CA
Period5/21/065/24/06

Keywords

  • Homeland security
  • Intelligence and security informatics
  • Mutual information

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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