Robustness of Presentation Attack Detection in Remote Identity Validation Scenarios

• URL: http://arxiv.org/abs/2602.00109v1
• Date: Mon, 26 Jan 2026 20:15:59 GMT
• Title: Robustness of Presentation Attack Detection in Remote Identity Validation Scenarios
• Authors: John J. Howard, Richard O. Plesh, Yevgeniy B. Sirotin, Jerry L. Tipton, Arun R. Vemury,
• Abstract summary: Presentation attack detection (PAD) subsystems are an important part of effective and user-friendly remote identity validation (RIV) systems.<n>This paper investigates the impact of low-light conditions and automated image acquisition on the robustness of commercial PAD systems using a scenario test of RIV.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Presentation attack detection (PAD) subsystems are an important part of effective and user-friendly remote identity validation (RIV) systems. However, ensuring robust performance across diverse environmental and procedural conditions remains a critical challenge. This paper investigates the impact of low-light conditions and automated image acquisition on the robustness of commercial PAD systems using a scenario test of RIV. Our results show that PAD systems experience a significant decline in performance when utilized in low-light or auto-capture scenarios, with a model-predicted increase in error rates by a factor of about four under low-light conditions and a doubling of those odds under auto-capture workflows. Specifically, only one of the tested systems was robust to these perturbations, maintaining a maximum bona fide presentation classification error rate below 3% across all scenarios. Our findings emphasize the importance of testing across diverse environments to ensure robust and reliable PAD performance in real-world applications.

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