Target vehicle identification for border safety using mutual information

Siddharth Kaza, Tao Wang, Hemanth Gowda, Hsinchun Chen

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

12 Scopus citations


The security of border and transportation systems is a critical component of the national strategy for homeland security. The security concerns at the border are not independent of law enforcement in border-area jurisdictions because information known by local law enforcement agencies may provide valuable leads useful for securing the border and transportation infrastructure. The combined analysis of law enforcement information and data generated by vehicle license plate readers at the international borders can be used to identify suspicious vehicles at ports of entry. This not only generates better quality leads for border protection agents but may also serve to reduce wait times for commerce, vehicles, and people as they cross the border. In this paper we use the mutual information concept to identify vehicles that frequently cross the border with vehicles that are involved in criminal activity. We find that the mutual information measure can be used to identify vehicles that can be potentially targeted at the border.

Original languageEnglish (US)
Title of host publicationITSC`05
Subtitle of host publication2005 IEEE Intelligent Conference on Transportation Systems, Proceedings
Number of pages6
StatePublished - 2005
Event8th International IEEE Conference on Intelligent Transportation Systems - Vienna, Austria
Duration: Sep 13 2005Sep 16 2005

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC


Other8th International IEEE Conference on Intelligent Transportation Systems

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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