Suspect vehicle identification for border safety

Siddharth Kaza, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Border safety is a critical part of national and international security. The U.S. Department of Homeland Security searches vehicles entering the country at land borders for drugs and other contraband. Customs and Border Protection (CBP) agents believe that such vehicles operate in groups and 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 vehicles that may be involved in criminal activity. CBP agents also suggest that criminal vehicles may cross at certain times or ports to try and evade inspection. In a partnership with border-area law enforcement agencies and CBP, we include these heuristics in the MI formulation and identify suspect vehicles using large-scale, real-world data collections. Statistical tests and selected cases judged by domain experts show that the heuristic-enhanced MI performs significantly better than classical MI in identifying pairs of potentially criminal vehicles. The techniques described can be used to assist CBP agents perform their functions both efficiently and effectively.

Original languageEnglish (US)
Title of host publicationStudies in Computational Intelligence
Pages305-318
Number of pages14
Volume135
DOIs
StatePublished - 2008

Publication series

NameStudies in Computational Intelligence
Volume135
ISSN (Print)1860949X

Fingerprint

National security
Statistical tests
Law enforcement
Inspection

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Kaza, S., & Chen, H. (2008). Suspect vehicle identification for border safety. In Studies in Computational Intelligence (Vol. 135, pp. 305-318). (Studies in Computational Intelligence; Vol. 135). https://doi.org/10.1007/978-3-540-69209-6_16

Suspect vehicle identification for border safety. / Kaza, Siddharth; Chen, Hsinchun.

Studies in Computational Intelligence. Vol. 135 2008. p. 305-318 (Studies in Computational Intelligence; Vol. 135).

Research output: Chapter in Book/Report/Conference proceedingChapter

Kaza, S & Chen, H 2008, Suspect vehicle identification for border safety. in Studies in Computational Intelligence. vol. 135, Studies in Computational Intelligence, vol. 135, pp. 305-318. https://doi.org/10.1007/978-3-540-69209-6_16
Kaza S, Chen H. Suspect vehicle identification for border safety. In Studies in Computational Intelligence. Vol. 135. 2008. p. 305-318. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-540-69209-6_16
Kaza, Siddharth ; Chen, Hsinchun. / Suspect vehicle identification for border safety. Studies in Computational Intelligence. Vol. 135 2008. pp. 305-318 (Studies in Computational Intelligence).
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