Two-Factor Biometric Verification with ECG: Two Cancelable Approaches.

Area of Science:

• Biometrics
• Cybersecurity
• Cardiology

Background:

• Biometric authentication uses unique physiological or behavioral traits for identity verification.
• Electrocardiograms (ECGs) are viable biometric traits, but ECG-based verification systems are underexplored.
• Existing biometric systems face privacy and security challenges.

Purpose of the Study:

• To propose two novel two-factor cancelable biometric verification schemes utilizing ECGs.
• To enhance security and privacy in biometric authentication through ECG-based recognition.
• To address the challenge of inter-beat variation in ECG biometric verification.

Main Methods:

• Development of two-factor cancelable biometric verification schemes.
• Utilizing bioconvolving and minimum average correlation energy filters for template creation.
• Implementing an interquartile range-based method for identity matching.
• Addressing inter-beat variation in ECG signals.

Main Results:

• Successfully constructed revocable and irreversible biometric templates.
• Achieved an equal error rate (EER) as low as 1% under optimal conditions.
• Demonstrated effective identity verification despite inter-beat variations.
• Mitigated privacy invasion and security concerns associated with ECG biometrics.

Conclusions:

• The proposed ECG biometric verification schemes provide a secure and privacy-preserving authentication method.
• The integration of cancelable templates enhances the security of ECG-based biometrics.
• The interquartile range method effectively handles inter-beat variations for reliable verification.