Securing Real-Time Data Transfer in Healthcare IoT Environments with Blockchain Technology

The increasing number of Internet of Things (IoT) devices in healthcare applications, particularly during emergencies, necessitates safe protocols for transmitting real-time data. Medical data are essential for healthcare applications, and reliance on IoT devices to control information flow necessitates the consideration of five critical areas. This work addresses the security challenges associated with the transmission and storage of copyrighted healthcare data, as well as the inadequacy of the present methods in facilitating real-time data transfer given the volume of data and network conditions. This research provides a theoretical framework for the secure and immediate offloading of computations in IoT healthcare systems. The objective is to implement secure communication and networking technologies to ensure the security and integrity of medical data, maintain confidentiality, and facilitate real-time transmission of information. The proposed framework is simulated in MATLAB for system model implementation. A blockchain network sandbox was established with the delegated proof-of- stake (DPoS) consensus method, supplemented by proof-of-work (PoW) and proof-of-validation (PoV) for enhanced security. To assess the efficacy of this framework, multiple test scenarios focused on the number of nodes, the volume of data, and the conditions of network connectivity. The results demonstrated the system's efficacy in facilitating the offloading of real-time data in IoT healthcare applications. The aforementioned study demonstrated that the framework exhibited rapid transaction processing, efficient resource use, and energy conservation while also enhancing secure data transmission across various network conditions. The findings confirm that the proposed architecture can effectively and securely transmit real-time data in IoT healthcare applications without jeopardizing data authenticity, privacy, or integrity. The system's ability to address security challenges and manage substantial data volumes under varying settings indicates that it can be effectively deployed in healthcare systems, particularly in critical situations.