Title: A computationally efficient authentication and key agreement scheme for multi-server switching in WBAN

Authors: Zisang Xu; Cheng Xu; Jianbo Xu; Xiangwei Meng

Addresses: Computer and Communication Engineer Institute, Changsha University of Science and Technology, Changsha, Hunan, 410114, China ' College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan, 410082, China ' School of Computer science and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China ' School of Computer science and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China

Abstract: In the wireless body area network (WBAN), the wearable device can monitor the patient's physiological information and send information to a server so that doctors can remotely diagnose the patient. As the patient's physiological information is sensitive, transmitting the data in the WBAN may reveal patient's privacy. In addition, in a multi-server environment, each server is usually independent of each other. However, most existing authentication schemes for WBAN either use a single-server model or do not consider multi-server switching issues. Therefore, we propose a computationally efficient mutual authentication and key agreement scheme for multi-server switching in WBAN. Our scheme ensures that patients can implement secure switching servers at any time in a multi-server environment. Our scheme proves to be secure under the Real-Or-Random model and ProVerif. In addition, compared with related schemes, our scheme solves the server switching problem while reducing the computational cost.

Keywords: authentication; cost-effective; cryptography; key agreement; multi-server switching; online re-registration; ProVerif; real-or-random model; security protocol; WBAN; wireless body area network.

DOI: 10.1504/IJSNET.2021.113839

International Journal of Sensor Networks, 2021 Vol.35 No.3, pp.143 - 160

Received: 30 Mar 2020
Accepted: 01 Jul 2020

Published online: 24 Mar 2021 *

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