Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network
Abstract Cancellable biometrics enabled us to develop robust authentication systems by replacing the storage of the original biometric template with another secured version. A technique called biometric salting uses a parameter (key) and an invertible function to transform the human biometrics featu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-IET
2021-11-01
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| Series: | IET Biometrics |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/bme2.12034 |
| _version_ | 1797422433832009728 |
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| author | Mayada Tarek Eslam Hamouda Sara El‐Metwally |
| author_facet | Mayada Tarek Eslam Hamouda Sara El‐Metwally |
| author_sort | Mayada Tarek |
| collection | DOAJ |
| description | Abstract Cancellable biometrics enabled us to develop robust authentication systems by replacing the storage of the original biometric template with another secured version. A technique called biometric salting uses a parameter (key) and an invertible function to transform the human biometrics features into a secured format that can be protected and stored securely in a biometric database system. The salting key plays a main role in the success of this transformation, which makes it robust or vulnerable to many security attacks. One of the main challenges that faces biometrics' researchers currently is how to design and protect such a salting key considering two basic measures: security and recognition accuracy. In this article, we propose unimodal‐Bio‐GAN, a reliable keyless biometric salting technique based on standard generative adversarial network (GAN). In unimodal‐Bio‐GAN, a random permuted version of the human biometric data is implicitly considered as a salting key and required only during the enrolment stage, which increases the system reliability to overcome different security attacks. The experimental results of unimodal‐Bio‐GAN using the CASIA Iris‐V3‐Internal database outperform the previous methods and its security efficiency is analysed using different attack types. |
| first_indexed | 2024-03-09T07:32:14Z |
| format | Article |
| id | doaj.art-6883917e38ea415e9280068a993a27ec |
| institution | Directory Open Access Journal |
| issn | 2047-4938 2047-4946 |
| language | English |
| last_indexed | 2024-03-09T07:32:14Z |
| publishDate | 2021-11-01 |
| publisher | Hindawi-IET |
| record_format | Article |
| series | IET Biometrics |
| spelling | doaj.art-6883917e38ea415e9280068a993a27ec2023-12-03T06:00:56ZengHindawi-IETIET Biometrics2047-49382047-49462021-11-0110665466310.1049/bme2.12034Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial networkMayada Tarek0Eslam Hamouda1Sara El‐Metwally2Department of Computer Science Mansoura University EgyptDepartment of Computer Science Mansoura University EgyptDepartment of Computer Science Mansoura University EgyptAbstract Cancellable biometrics enabled us to develop robust authentication systems by replacing the storage of the original biometric template with another secured version. A technique called biometric salting uses a parameter (key) and an invertible function to transform the human biometrics features into a secured format that can be protected and stored securely in a biometric database system. The salting key plays a main role in the success of this transformation, which makes it robust or vulnerable to many security attacks. One of the main challenges that faces biometrics' researchers currently is how to design and protect such a salting key considering two basic measures: security and recognition accuracy. In this article, we propose unimodal‐Bio‐GAN, a reliable keyless biometric salting technique based on standard generative adversarial network (GAN). In unimodal‐Bio‐GAN, a random permuted version of the human biometric data is implicitly considered as a salting key and required only during the enrolment stage, which increases the system reliability to overcome different security attacks. The experimental results of unimodal‐Bio‐GAN using the CASIA Iris‐V3‐Internal database outperform the previous methods and its security efficiency is analysed using different attack types.https://doi.org/10.1049/bme2.12034biometrics (access control)cryptographyfeature extractionfingerprint identificationiris recognitionsecurity of data |
| spellingShingle | Mayada Tarek Eslam Hamouda Sara El‐Metwally Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network IET Biometrics biometrics (access control) cryptography feature extraction fingerprint identification iris recognition security of data |
| title | Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network |
| title_full | Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network |
| title_fullStr | Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network |
| title_full_unstemmed | Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network |
| title_short | Unimodal‐Bio‐GAN: Keyless biometric salting scheme based on generative adversarial network |
| title_sort | unimodal bio gan keyless biometric salting scheme based on generative adversarial network |
| topic | biometrics (access control) cryptography feature extraction fingerprint identification iris recognition security of data |
| url | https://doi.org/10.1049/bme2.12034 |
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