1. Multimodal cancelable biometric authentication system based on EEG signal for IoT applications.
- Author
-
Salama, Gerges M., El-Gazar, Safaa, Omar, Basma, and Hassan, A. A.
- Abstract
Nowadays, new technologies such as Internet of Things (IoT) applications depend on biometrics for authentication and identity verification. These biometrics contain confidential information about the user. It is necessary to keep these biometrics in a secure template. The Cancelable Biometric System (CBS) aims to protect biometric traits by preserving them in an intended distorted template. This paper presents a cancelable multimodal biometric authentication system based on optical encryption algorithms and watermarking. The new trend in biometric authentication systems is to use Electroencephalography (EEG) signals. The proposed CBS is based on merging the EEG signal with another biometric image, then the obtained data is encrypted by optical encryption software. Double Random Phase Encoding (DRPE), Optical Scanning Holography (OSH), cascade DRPE-OSH, and cascade OSH-DRPE are applied separately to encrypt the merged data and get the final cancelable template. Simulation results prove the high accuracy and efficiency of the proposed system, as the Equal Error Rate (EER) value is close to 0 and the Area under the Receiver Operator Characteristic (AROC) is close to 1. Simulation results indicate the performance stability of the proposed system in the presence of different types of noise and attacks. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF