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- Title
Implementation of quaternion mathematics for biometric security.
- Authors
Khallaf, Fatma; El-Shafai, Walid; El-Rabaie, El-Sayed M.; Nasr, Mahmoud; Essam, Mohammed; Shoukralla, E. S.; Abd El-atty, Saied M.; Abd El-Samie, Fathi E.
- Abstract
Cancellable biometrics is an important trend in biometric security systems, allowing for intentional distortions or variations in the original biometric data to be used for authentication, while preserving privacy of users and security of the original data. This paper presents two cancellable biometric recognition algorithms based on quaternion mathematics. The first algorithm depends on the Fractional Fourier transform (FRFT) with quaternion mathematics to induce intentional distortions in biometric data, while the second algorithm relies on quaternion rotation to achieve the desired level of distortion. Both algorithms are evaluated using Equal Error Rate (EER) and Area under Receiver Operating Characteristic curve (AROC). The simulation results indicate that both algorithms achieve EER values close to 0 and AROC values close to 1, demonstrating their effectiveness and reliability for cancellable biometric recognition. The proposed cancellable biometric recognition algorithms are intended to preserve privacy of users and security of biometric data, while maintaining high levels of accuracy and performance. The use of quaternion mathematics allows for intentional distortions to be introduced in a controlled and secure manner, ensuring that the original biometric data remains protected from either hacking or unauthorized access. In conclusion, the proposed cancellable biometric recognition algorithms based on quaternion mathematics are reliable and effective solutions for biometric security, providing both security and privacy preservation within the biometric authentication process.
- Subjects
RECEIVER operating characteristic curves; BIOMETRIC identification; SECURITY systems; QUATERNIONS; ERROR rates; FOURIER transforms
- Publication
Multimedia Tools & Applications, 2024, Vol 83, Issue 30, p74785
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-023-16479-3