Finger vein secure biometric template generation based on deep learning
| Autor: | Jian Shen, Yi Liu, Zhusong Liu, Chongzhi Gao, Jie Ling |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Password
Authentication Biometrics business.industry Computer science Deep learning Data_MISCELLANEOUS 020206 networking & telecommunications 02 engineering and technology Computer security computer.software_genre Finger vein recognition Theoretical Computer Science 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Geometry and Topology Artificial intelligence business computer Software |
| Zdroj: | Soft Computing. 22:2257-2265 |
| ISSN: | 1433-7479 1432-7643 |
| Popis: | Leakage of unprotected biometric authentication data has become a high-risk threat for many applications. Lots of researchers are investigating and designing novel authentication schemes to prevent such attacks. However, the biggest challenge is how to protect biometric data while keeping the practical performance of identity verification systems. For the sake of tackling this problem, this paper presents a novel finger vein recognition algorithm by using secure biometric template scheme based on deep learning and random projections, named FVR-DLRP. FVR-DLRP preserves the core biometric information even with the user’s password cracked, whereas the original biometric information is still safe. The results of experiment show that the algorithm FVR-DLRP can maintain the accuracy of biometric identification while enhancing the uncertainty of the transformation, which provides better protection for biometric authentication. |
| Databáze: | OpenAIRE |
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