Iris Presentation Attack: Assessing the Impact of Combining Vanadium Dioxide Films with Artificial Eyes
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Abstract (arXiv)
Iris recognition systems, operating in the near infrared spectrum (NIR), have demonstrated vulnerability to presentation attacks, where an adversary uses artifacts such as cosmetic contact lenses, artificial eyes or printed iris images in order to circumvent the system. At the same time, a number of effective presentation attack detection (PAD) methods have been developed. These methods have demonstrated success in detecting artificial eyes (e.g., fake Van Dyke eyes) as presentation attacks. In this work, we seek to alter the optical characteristics of artificial eyes by affixing Vanadium Dioxide (VO2) films on their surface in various spatial configurations. VO2 films can be used to selectively transmit NIR light and can, therefore, be used to regulate the amount of NIR light from the object that is captured by the iris sensor. We study the impact of such images produced by the sensor on two state-of-the-art iris PA detection methods. We observe that the addition of VO2 films on the surface of artificial eyes can cause the PA detection methods to misclassify them as bonafide eyes in some cases. This represents a vulnerability that must be systematically analyzed and effectively addressed.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 49 references that are in the map. First posted on arXiv 21 Nov 2023.
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7 of 49 references.
References · 7
- 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,733
- 2016Densely Connected Convolutional Networkscited by 6,720
- 2020Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Editioncited by 27
- 2020D-NetPAD: An Explainable and Interpretable Iris Presentation Attack Detectorcited by 26
- 2018Presentation Attack Detection for Iris Recognition: An Assessment of the State of the Artcited by 24
- 2023Iris Liveness Detection Competition (LivDet-Iris) -- The 2023 Editioncited by 13
- 2022State Of The Art In Open-Set Iris Presentation Attack Detectioncited by 1
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