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- W3126279905 abstract "As a recent distribution of mobile and fintech systems, user authentication via biometric recognition has been widely used. Specifically, deep learning-based fingerprint recognition methods became popular due to their high accuracy in fingerprint liveness detection. However, existing deep learning-based approaches contain inherent vulnerabilities such as adversarial attack. In this paper, we propose a new method for generative adversarial attack on fingerprint recognition systems. Our method generates fingerprint images which effectively break existing deep learning-based fingerprint recognition systems while maintaining real-looking appearance of target fingerprints." @default.
- W3126279905 created "2021-02-15" @default.
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- W3126279905 date "2021-01-13" @default.
- W3126279905 modified "2023-10-16" @default.
- W3126279905 title "Generative Adversarial Attacks on Fingerprint Recognition Systems" @default.
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- W3126279905 doi "https://doi.org/10.1109/icoin50884.2021.9333904" @default.
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