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Semantic Scholar · Article (Decision Analytics)
Insights for Critical Alarm-Based Warning Systems from a Risk Analysis of Commercial Aviation Passenger Screening
Attribution
This is the abstract and citation. Full text lives at Semantic Scholar — we link out rather than host. All credit to the authors and Decision Analytics.
Abstract
Verbatim from Semantic Scholar. Not paraphrased, not summarized.
The Transportation Security Administration (TSA) recently commissioned a risk analysis of the passenger threat vector in which an adversary gains access through the screening checkpoint. The goal of the project was to provide insights to the TSA to improve both safety and resource allocation as they continue to develop new security procedures in a constantly evolving threat environment. The result was a probabilistic risk model to support the TSA as they plan future safety and resource allocations procedures. Because aviation passenger screening involves highly sensitive information, we discuss the insights gained from the study that are applicable for other highly critical security systems that rely on alarm-based warning technologies to detect anomalies.
Authors
- R. Dillon
- William J. Burns
- R. John
Keywords
- Computer Science
- Engineering
- Political Science
Citation: R. Dillon, William J. Burns, R. John (2018). Insights for Critical Alarm-Based Warning Systems from a Risk Analysis of Commercial Aviation Passenger Screening. Decision Analytics. Semantic Scholar ID d71248e57cbc04f6ef9d8b0693007c483d57644b. https://doi.org/10.1287/deca.2018.0369 ↗