Designing a Healthcare-Enabled Software-Defined Wireless Body Area Network Architecture for Secure Medical Data and Efficient Diagnosis

Abstract

In the struggle against population aging, chronic diseases, and a lack of medical facilities, the emergence of Wireless Body Area Networks (WBANs) technology has ushered in optimism. WBANs use a variety of wearable and implanted biosensor nodes to constantly monitor physiological parameters such as oxygen saturation (SpO2), electrocardiogram (ECG), electromyography (EMG), electroencephalogram (EEG), blood pressure, respiration rate, body temperature, and pulse rate. Importantly, these vital signs are communicated to a doctor over a public network, who can diagnose ailments remotely and efficiently. Among these communications, the security and privacy of patients are the prime concerns while transferring data over an open wireless channel from biosensor nodes to a Medical Server (MS) through a Base Station (BS) for efficient medical diagnosis. Finding an effective security strategy for patients which rely on WBANs to monitor their health information is a huge challenge due to the confined nature of the WBANs environment. To tackle the above challenges, in this research, a new, efficient, and secure healthcare-enabled software-defined WBANs architecture based on Schnorr signcryption and Hyperelliptic Curve Cryptography (HECC) is suggested in which the SDN technology is integrated into WBANs. By separating the control and data planes in an efferent manner, SDN technology allows you to control and manage the network in a programmable manner. The main features of SDN, such as its programmability, flexibility, and centralized control, make it a simple and scalable network. In this research, first, a Software-Defined Wireless Body Area Networks (SD-WBANs) architecture has been designed, and then a lightweight Schnorr signcryption with Hyperelliptic Curve Cryptography (HECC) has been proposed to preserve sensitive patient data security during transmission on public networks. Moreover, a well-known Multicriteria Decision-Making (MCDM) approach known as Evaluation Based on Distance from Average Solution (EDAS) is also used to demonstrate the success of the suggested system. According to the performance analysis, the suggested approach beats previous state-of-the-art techniques in terms of computation cost, communication overhead, storage cost, and energy usage.