Utilization of adaptive filtering for biometric template masking

• Published in: Optical and quantum electronics Vol. 55; no. 7
• Main Authors: Naeem, Ensherah A., Saied, Ayat, EL-Fishawy, Adel S., Rihan, Mohamad, El-Samie, Fathi E. Abd, El-Banby, Ghada M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-07-2023; Springer Nature B.V
• Subjects: Adaptive filters; Biometrics; Characterization and Evaluation of Materials; Computer Communication Networks; Data compression; Discrete cosine transform; Electrical Engineering; Lasers; Masking; Optical Devices; Optics; Photonics; Physics; Physics and Astronomy; Recognition; Security; Theft; Utilization; Simultaneous compression; DRPE; Adaptive filter; Cancelable biometrics; Multi-biometric systems
• ISSN: 0306-8919; 1572-817X
• DOI: 10.1007/s11082-022-04456-3

Currently, security enhancement of biometric systems is an important issue that deserves consideration. This is attributed to the threats facing traditional common recognition systems, which depend on Personal Identification Numbers (PINs) that can be stolen easily. Utilization of original biometrics to access user services may lead to loss of the biometrics forever, if hacking attempts succeed in gaining access to the storage database of original templates. To address this concern and to avoid the utilization of original biometrics, we keep them away from being compromised through the utilization of cancelable biometric templates. This paper introduces a novel methodology for user authentication with multiple biometrics to generate distorted non-invertible cancelable templates to be stored in the database. The proposed framework begins with Discrete Cosine Transform (DCT) to achieve data compression in a multi-biometric scenario. After that, Double Random Phase Encoding (DRPE) is applied to increase the security level of the generated distorted encrypted templates. Finally, an adaptive filter is used to generate masking patterns for biometric templates. The patterns are uncorrelated, which improves the security level against identity theft and provides better identification performance. Simulation results give a promising performance of the proposed cancelable biometric recognition framework with a high Area under the Receiver Operating Characteristic curve (
AROC
) of 99.9824% and an Equal Error Rate (
EER
) of 0%. In addition, other statistical evaluation metrics have been considered to reveal superiority of the proposed framework.