Cancelable ECG Biometrics Using Compressive Sensing-Generalized Likelihood Ratio Test
Abstract
Electrocardiogram (ECG) has been investigated as promising biometrics, but it cannot be canceled and re-used once compromised just like other biometrics. We propose methods to overcome the issue of irrevocability in ECG biometrics without compromising performance. Our proposed cancelable user authentication uses a generalized likelihood ratio test (GLRT) based on a composite hypothesis testing in compressive sensing (CS) domain. We also propose...
Paper Details
Title
Cancelable ECG Biometrics Using Compressive Sensing-Generalized Likelihood Ratio Test
Published Date
Jan 1, 2019
Journal
Volume
7
Pages
9232 - 9242
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