# Wearable Sensors for Vital Signs Measurement: A Survey
## 3 Intelligent Prospect of Wearable Medical Sensors
### Intelligent Prospective Applications of Wearable Medical Sensors  
#### 3.2.1 Prospects for Information Security of Wearable Medical Sensors  
A wearable medical sensor system is mainly used to monitor human physiological parameters, which is a body sensor network (BSN). BSN technology, based on IoT, is one of the most important technologies in modern medical systems. It is a collection of low-power, lightweight wireless sensor nodes that are used to monitor human body functions and the surrounding environment [50]. Since human sensor network nodes are used to collect sensitive human information and may operate in harsh environments, strict security mechanisms are required to prevent malicious interaction with the system. Therefore, security research into human medical sensor networks has attracted many scholars' attention. [PERSON] et al. (2018) found that in medical applications, the 5G-inspired Industrial Internet of Things (IIoT) paradigm enables users to interact with various types of sensors through a secure wireless medical sensor network (WMSN). However, the user's self-verification before each interaction is a lengthy and time-consuming process, which can interfere with residents' activities and reduce the overall performance of the medical system. In response to this problem, a context-sensitive seamless identity provisioning (CSIP) framework was proposed. The framework used a secure mutual authentication method of hash and global assertion value, which demonstrated that the mechanism could achieve the main security goal of WMSN in a short time [51]. [PERSON] et al. (2019) studied, in detail, the security issues relating to the perception layer of the Internet of Things, and described the key components of the Internet of Things (i.e., architecture, standards, and protocols) in the security environment of the perception layer, and then the security requirements of the Internet of Things. Second, after describing the hierarchical security of the general Internet of Things, two key enabling technologies of the perception layer, namely RFID and sensor networks, were discussed. Finally, open research issues and challenges related to the perception layer were identified and analyzed [52]. [PERSON] et al. (2020) developed a double watermark, based on compression and then encryption, to protect the EPR (electronic patient records) data in the medical system, which produced some important characteristics. After using medical sensors to collect a large amount of medical data, experiments showed that the proposed method has the ability of intelligent medical treatment, and compared with the existing technology, the proposed work provides better performance in terms of robustness and safety [53]. [PERSON] et al. (2020) introduced several trust models complying with the security requirements of IoT systems; they studied the security issues and requirements of IoT, the routing protocol for low power, and lossy network (RPL) routing protocols under various attacks, such as black holes, deception, hierarchy, etc. In addition, various mitigation methods and the meanings of the trust model in the Internet of Things to secure routing were analyzed. Finally, they measured trust in the IoT environment, including open issues and research challenges, and the meaning of trust as a security paradigm for IoT networks and routing protocols to gain a deeper understanding [54]. [PERSON] (2021) focused on the problem of energy imbalance in the infusion network, introduced the calculation method of network energy consumption under the direct transmission and minimum energy multi-hop routing protocol, and designed an improved network structure model to increase the communication scale. It was found that this method realized data aggregation and data transmission, and that the development of the monitoring system application platform adopted software technology.