论文标题
使用ECG的两因素生物识别验证：两种可取消的方法
Two-Factor Biometric Verification with ECG: Two Cancelable Approaches
论文作者
论文摘要
生物识别认证依赖于个人的生理或行为特征来验证其身份，然后在不记住任何事情的情况下授予对系统或设备的访问权限。尽管心电图（ECG）被认为是一种生物特征，但是很少考虑以验证模式运行的ECG生物识别系统。这项研究提出了两个可取消的生物识别验证方案，该方案可以使用ECG识别身份。可以使用生物涉及和最小平均相关能量生物识别过滤器，可以构建可撤销和不可逆模板，以避免与ECG生物识别识别相关的隐私入侵和安全问题。采用基于四分位间范围的方法来确定是否存在身份匹配，从而在基间变化的影响下实现身份验证。实验结果表明，当正确解决beat差异时，提出的方案可以达到相等的错误率1％。
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.
