  Biometric authentication relies on an individual's physiological or
behavioral traits to verify their identity before granting access permission to
a system or device without remembering anything. Although electrocardiograms
(ECGs) have been considered a biometric trait, an ECG biometric recognition
system that operates in verification mode is rarely considered. This study
proposes two two-factor cancelable biometric verification schemes that enable
identity recognition using ECGs. Using bioconvolving and minimum average
correlation energy biometric filters, revocable and irreversible templates can
be constructed to avoid privacy invasion and security concerns associated with
ECG biometric recognition. An interquartile range-based method is adopted to
determine if an identity match exists, enabling identity verification under the
influence of inter-beat variation. The experimental results indicated that the
proposed schemes could achieve an equal error rate as low as 1% when the
inter-beat variation was properly addressed.
