As one of the crucial components in the emerging internet of things (IoT), wireless body area networks (WBANs) is capable of monitoring vital physiological and behavioral information of users through wearable sensors, offering a new paradigm for the next-generation healthcare systems. However, due to the inherent open wireless communicating characteristics, security and privacy issues for WBANs communication remain unsolved. Note that the deployed WBANs sensors are resource-restrained entities, which restricts its wide applications in medical environment. In this case, effective authentication scheme with efficient group key management strategy is of great significance. Moreover, with comparatively large computation ability and storage capacity, smartphone is able to perform as the vital data processing gateway for WBANs, especially in the upcoming 5G network implementation with superior transmission quality and speed. Furthermore, the WBAN sensors are responsible for continuous physiological monitoring, where the acquired biometric features could be adopted to the authentication process. For the above consideration, a secure certificateless biometric authentication and group key management for WBAN scenarios is proposed in this paper. In our design, user's smartphone takes the role of personal controller (PC) in traditional WBANs structure. The representative features of the gathered electrocardiogram (ECG) records are applied as the distinctive biometric parameter during authentication procedure. Hence efficient authentication towards participating sensors is enabled. Subsequently, fast group key management among all validated sensors is presented, where small modification is required for dynamic key updating mechanism in sensor side. Security analysis indicates that the proposed protocol can achieve desired security properties and provide resistance to various attacks. Performance analysis demonstrates that the proposed protocol is efficient compared with the state-of-the-art WBAN authentication schemes.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)