Dual-Factor WBAN Enhanced Authentication System Based on Iris and ECG Descriptors

Abstract

At present, COVID-19 is still spreading and affecting millions of people worldwide. Minimizing the need for travel can significantly reduce the probability of infection and improve patients’ quality of life. The wireless body area network (WBAN) transmits the patients’ physiological data to the doctor remotely through the sensors in a way that minimizes physical contact with others. However, existing WBAN security authentication schemes have a core limitation that includes weak authentication performance and overconsumption of resources that precludes their widespread adoption in practical applications. Therefore, in this article, an enhanced dual-factor authentication system that addresses the mentioned drawbacks is proposed for securing WBAN resources. By combining iris and electrocardiogram (ECG) features, users would be required to pass the first-level iris authentication before performing the second-level ECG authentication, thus enhancing the overall security scheme of a WBAN system. Furthermore, we examined the existing inter-pulse-interval (IPI) encoding methods and propose a more efficient ECG IPI encoding algorithm, which can effectively shorten the encoding time without affecting the overall encoding performance. Finally, extensive experiments were performed to verify the performance of the proposed dual-factor iris and ECG-based WBAN authentication system using public iris and ECG databases. The experimental results show that the false acceptance rate (FAR) is close to 0.0%, and the false rejection rate (FRR) is close to 3.2%. Findings from this study suggest that the proposed dual-factor authentication scheme could aid the adequate deployment of security schemes to protect WBAN resources in practical applications.