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An Analysis of the Impact of Passenger Profiling for Transportation Security

Author

Listed:
  • Huseyin Cavusoglu

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083)

  • Byungwan Koh

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083)

  • Srinivasan Raghunathan

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083)

Abstract

The proponents of airline passenger profiling claim that profiling will reduce the cost of security, improve the detection of attackers, increase the reliability of signals from screening devices, and reduce the inconvenience to normal passengers. In this paper we show that if the Transportation Security Administration (TSA) manually inspects all those passengers classified as likely attackers and sends others through a screening system, as it did when it deployed the Computer Assisted Passenger Prescreening System (CAPPS), then it is superior to no profiling on all four performance measures if and only if the quality of the profiler vis-à-vis that of the screening system is sufficiently high. If the quality of the screening device is sufficiently high, profiling could be detrimental on all four performance measures. On the other hand, if the TSA deploys two screening devices along with the profiler---each screening device optimally configured for each of the two groups of passengers---then profiling improves the reliability of screening device signals, reduces the inconvenience caused to normal passengers, and improves the social welfare even when quality of the screening device is high. One of the implications of our findings is that the security architecture used by the TSA when it deployed CAPPS could provide a strong support to the arguments by some against the use of profiling; however, if the TSA deploys a two-screening device architecture, it might not only blunt the criticism that profiling is discriminatory but also benefit normal passengers and overall society economically.

Suggested Citation

  • Huseyin Cavusoglu & Byungwan Koh & Srinivasan Raghunathan, 2010. "An Analysis of the Impact of Passenger Profiling for Transportation Security," Operations Research, INFORMS, vol. 58(5), pages 1287-1302, October.
    • Handle: RePEc:inm:oropre:v:58:y:2010:i:5:p:1287-1302
    DOI: 10.1287/opre.1090.0793
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    References listed on IDEAS

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    2. Sushil Gupta & Martin K. Starr & Reza Zanjirani Farahani & Mahsa Mahboob Ghodsi, 2020. "Prevention of Terrorism–An Assessment of Prior POM Work and Future Potentials," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1789-1815, July.
    3. Huseyin Cavusoglu & Young Kwark & Bin Mai & Srinivasan Raghunathan, 2013. "Passenger Profiling and Screening for Aviation Security in the Presence of Strategic Attackers," Decision Analysis, INFORMS, vol. 10(1), pages 63-81, March.
    4. Nie, Xiaofeng, 2019. "The impact of conditional dependence on checked baggage screening," European Journal of Operational Research, Elsevier, vol. 278(3), pages 883-893.
    5. Hoogstrate, André J. & Klaassen, Chris A.J., 2015. "Information weighted sampling for detecting rare items in finite populations with a focus on security," European Journal of Operational Research, Elsevier, vol. 241(3), pages 880-887.
    6. Kirschenbaum, Alan (Avi), 2013. "The cost of airport security: The passenger dilemma," Journal of Air Transport Management, Elsevier, vol. 30(C), pages 39-45.
    7. Yonghua Ji & Subodha Kumar & Vijay Mookerjee, 2016. "When Being Hot Is Not Cool: Monitoring Hot Lists for Information Security," Information Systems Research, INFORMS, vol. 27(4), pages 897-918, December.
    8. Wang, Xiaofang & Zhuang, Jun, 2011. "Balancing congestion and security in the presence of strategic applicants with private information," European Journal of Operational Research, Elsevier, vol. 212(1), pages 100-111, July.
    9. Yan, Xihong & Ren, Xiaorong & Nie, Xiaofeng, 2022. "A budget allocation model for domestic airport network protection," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).

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