Cancelable Biometrics Technique for Iris Recognition
Title | Cancelable Biometrics Technique for Iris Recognition |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Ali, M. A. M., Tahir, N. M. |
Conference Name | 2018 IEEE Symposium on Computer Applications Industrial Electronics (ISCAIE) |
Date Published | apr |
Keywords | Bath-A dataset, Bioinformatics, biometric data, biometric encryption, cancelable biometrics, cancelable biometrics features, cancelable biometrics method, cryptography, Databases, decryption noninvertible transformation, Encryption, encryption noninvertible transformation, feature extraction, Iris recognition, Metrics, Non-linear Quadratic kerne, pubcrawl, recognition rate, reliability, resilience, Resiliency, Scalability, support vector machine |
Abstract | Iris recognition is one of the most reliable biometrics for identification purpose in terms of reliability and accuracy. Hence, in this research the integration of cancelable biometrics features for iris recognition using encryption and decryption non-invertible transformation is proposed. Here, the biometric data is protected via the proposed cancelable biometrics method. The experimental results showed that the recognition rate achieved is 99.9% using Bath-A dataset with a maximum decision criterion of 0.97 along with acceptable processing time. |
URL | https://ieeexplore.ieee.org/document/8405512 |
DOI | 10.1109/ISCAIE.2018.8405512 |
Citation Key | ali_cancelable_2018 |
- encryption noninvertible transformation
- support vector machine
- Scalability
- Resiliency
- resilience
- Reliability
- recognition rate
- pubcrawl
- Non-linear Quadratic kerne
- Metrics
- Iris recognition
- feature extraction
- Bath-A dataset
- encryption
- decryption noninvertible transformation
- Databases
- Cryptography
- cancelable biometrics method
- cancelable biometrics features
- cancelable biometrics
- biometric encryption
- biometric data
- bioinformatics