# Security in Wireless Body Sensor Network: A Multivocal Literature Study
## 2 Security in Wireless Body Sensor Network  
A patient's medical state can be monitored using telemonitoring systems. The rising expense of medical services, the increasing elderly population, and the rise in chronic disease patients worldwide are increasing demands for alternatives in the healthcare sector. Due to these challenges, conventional health care cannot achieve the needed flexibility. As a result, high-performance, low-cost, and appropriate care solutions are required. The wireless body sensor network (WBSN) is a wireless platform that allows sensors attached to a patient's body to communicate to monitor the body's essential parameters and surroundings. The use of wireless sensor nodes in public healthcare tracking opens doors for delivering superior patient care. For example, at-risk individuals with a background of heart problems or aged individuals who live independently can be monitored using various sensors. These sensors allow physicians to diagnose diseases more efficiently by providing ongoing, long-term tracking in an invisible manner [10]. A body sensor network or BSN is a collection of sensors placed on the person's body to gather physiological signals [11]. In recent research and industry, the design and implementation of these WBSN approaches to health monitoring have received increased interest. This focus is primarily driven by the high cost of health care and recent advances in the manufacturing of micro-health applications and new technologies, such as the internet of things (IoT), contributing to the 5G main obstacles. An explicit approach to handling the basic software design and validation should be advantageous for building and maintaining these systems. At various spots, the sensors observe and compare the circumstances. Environmental (e.g., pollution levels, weather, and moisture) and essential human functions are typical examples (e.g., heart and brain signals). A WSN can sense, process, and communicate. To acquire data on the centralized environment, diverse WSN-based monitoring applications have been created in many application sectors. Defense applications [11], global warming tracking applications [12], applications in submarine networking [13], and applications in health monitoring [14] are only a few examples. Regardless of these applications, security has become a significant challenge. The system must ensure the security and privacy of the collected individual health data. Decomposing activity results in an increase in the platform's flaws and renders it more complex to implement the security architecture. This has resulted in a number of BSN privacy discussions, the most important of which are discussed and taken in context hereinafter [15]. The developers in [16] suggested a secure platform based on heart rate frequency. They used the measurements of the inter-pulse periods to build binary patterns from the beats. In 8 s, they generated a 128-bit sequence using ECG records from the MIT-BIH arrhythmia dataset. As a result, they could minimize the time it took to generate a random sequence of bits. The fundamental issue of employing a heartbeat as a security measure is inconsistent over time. The person's health records should be protected to avoid information misuse, and the patients should be able to reach the practitioner at the appropriate time and without delay. Secure key management in WBAN (SEKBAN) is an innovative approach that addresses security issues at three stages. By constructing keys relying on the ECG signal, this suggested technique protects the data's privacy [17]. Depending on the ECG monitor, the researchers in [17] offer a body sensor network encryption and user authentication (BSN-EUA) approach. The BSN-EUA method provides fingerprint recognition for identity verification, and all of a person's health-related activities are logged on the handset. The descriptive properties of the electrocardiogram (ECG) are employed as a recognized fingerprint feature all through the access control mechanism.