Wearable devices (WDs) adopting advanced microsensors and IoT technology are facing severe security risks in the process of building wearable healthcare monitoring system. In particular, new requirements are proposed for the security of the identity authentication and key agreement protocol as well as the consumption of computing resources for WDs, such as replay attack, modification attack, server-spoofing attack, privileged-insider attack, and denial-of-service attack. To satisfy such requirements, cloud-assisted EC password authenticated key exchange (CEPAK), an identity dynamic authentication and key agreement protocol, is proposed, and it uses a cloud-assisted authentication service and elliptic curve algorithm. The capability of CEPAK protocol is analyzed to deal with network attack and consumption of computing resources and communication resources. It is shown that on the basis of satisfying the security requirements of the system, the cloud-assisted authentication server can greatly share

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Background During cardiac emergency medical treatment, reducing the incidence of avoidable adverse events, ensuring the safety of patients, and generally improving the quality and efficiency of medical treatment have been important research topics in theoretical and practical circles. Objective This paper examines the robustness of the decision-making reasoning process from the overall perspective of the cardiac emergency medical system. Methods The principle of robustness was introduced into our study on the quality and efficiency of cardiac emergency decision making. We propose the concept of robustness for complex medical decision making by targeting the problem of low reasoning efficiency and accuracy in cardiac emergency decision making. The key bottlenecks such as anti-interference capability, fault tolerance, and redundancy were studied. The rules of knowledge acquisition and transfer in the decision-making process were systematically analyzed to reveal the core role of knowledge reasoning. Results The robustness threshold method was adopted to construct the robustness criteria group of the system, and the fusion and coordination mechanism was realized through information entropy, information gain, and mutual information methods. Conclusions A set of fusion models and robust threshold methods such as the R2CMIFS (treatment mode of fibroblastic sarcoma) model and the RTCRF (clinical trial observation mode) model were proposed. Our study enriches the theoretical research on robustness in this field.

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