Computer Science > Computer Vision and Pattern Recognition
arXiv:2403.12047 (cs)
[Submitted on 20 Nov 2023]
Title:Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems
View a PDF of the paper titled Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems, by Sudipta Banerjee and 5 other authors
View PDFHTML (experimental)Abstract:A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security. We focus on dictionary attacks at the template level, specifically the IrisCodes used in iris recognition systems. We present an hitherto unknown vulnerability wherein we mix IrisCodes using simple bitwise operators to generate alpha-mixtures - alpha-wolves (combining a set of "wolf" samples) and alpha-mammals (combining a set of users selected via search optimization) that increase false matches. We evaluate this vulnerability using the IITD, CASIA-IrisV4-Thousand and Synthetic datasets, and observe that an alpha-wolf (from two wolves) can match upto 71 identities @FMR=0.001%, while an alpha-mammal (from two identities) can match upto 133 other identities @FMR=0.01% on the IITD dataset.
| Comments: | 8 pages, 5 figures, 13 tables, Workshop on Manipulation, Adversarial, and Presentation Attacks in Biometrics, Winter Conference on Applications of Computer Vision |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2403.12047 [cs.CV] |
| (orarXiv:2403.12047v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2403.12047 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems, by Sudipta Banerjee and 5 other authors
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