University of California—Irvine Enhancing Aviation Security through the use of Signal Detection Theory Nicholas Scurich University of California—Irvine Irvine, CA Problem Statement and Objective: The TSA uses Secure Flight ™ to assess the risk of aviation passengers and classify each passenger into one of three risk groups: high risk; low risk; unknown risk. Little is known about how risk estimates are translated into a risk classification. This project will systematically investigate the decision making process, integrate the value tradeoffs of multiple different stakeholder groups, and ultimately create a software tool that can be used to establish cut-points that are appropriate, systematic, and acceptable across stakeholder groups. Methodology and Data Requirements: The methodology involves an innovative application of Signal Detection Theory. Inputs for the model will be determined from TSA documents (i.e., the discriminability of the Secure Flight algorithm) and value tradeoffs will be elicited from relevant stakeholders. Impact Statement and Relevance to DHS Roles and Responsibilities: Systematically studying the cut-points used by the TSA is vital to security as they determine the relative rates of false negative and positive misclassifications. We simply do not know what these tradeoffs currently are, nor whether they are in accord with what different stakeholder groups believe are acceptable. The project addresses these lacunas. Depending on the findings, it is possible that TSA precheck could be expanded to include more individuals, which would reduce overcrowding at airport checkpoints. Both Scurich and John (Co-PI) will be responsible for all aspects of this project. Timeline and Deliverables: Year 1: Report demonstrating the application of Signal Detection Theory to aviation security, along with analyses that reveal the implicit value-tradeoffs of the de facto decision thresholds for low, high, unknown risk. 30 days: refine proposal; speak with subject matter experts (SMEs) at TSA. 60 days: submit IRB application; conduct literature review. 90 days: begin to formulate model; continue working with SMEs. Year 2: Travel to conduct in-person value elicitations from relevant stakeholders regarding acceptable levels of false positive/negative errors. These values will be integrated into a model to elucidate optimal decision thresholds – a customized solution. A software tool will be delivered so that the methodology and findings can be easily implemented and ported to different security contexts and applications.