Detecting Concealment of Intent in Transportation Screening: A Proof of Concept

This paper examines security checkpoints and the issue of detecting intent and deception. The authors introduce a multidisciplinary theoretical model of intent concealment and propose three verbal and nonverbal automated methods for detecting intent: message feature mining, speech act profiling, and kinesic analysis. The authors also review a program of empirical research supporting this model, including several previously published studies and the results of a proof-of-concept study. The model is supported by demonstrating that aspects of intent can be detected at a rate that is higher than chance. The paper concludes with a discussion regarding how the proposed methods could be applied to an airport-screening scenario.

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01142677
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Files: BTRIS, TRIS
  • Created Date: Oct 5 2009 8:02PM