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The Internet of Medical Things (IoMT) technology’s fast advancements aided smart healthcare systems to a larger extent. IoMT devices, on the other hand, rely on centralized processing and storage systems because of their limited computational and storage capacity. The reliance is susceptible to a single point of failure (SPoF) and erodes the user control over their medical data. In addition, Cloud models result in communication delays, which slow down the system’s overall reaction time. To overcome these issues a decentralized distributed smart healthcare system is proposed that eliminates the SPoF and third-party control over healthcare data. Additionally, the proposed Fortified-Chain 2.0 uses a blockchain-based selective sharing mechanism with a mutual authentication technique to solve the issues, such as data privacy, security, and trust management in decentralized peer-to-peer healthcare systems. Also, we suggested a hybrid computing paradigm to deal with latency, computational, and storage constraints. A novel distributed machine learning (ML) module named random forest support vector machine (RFSVM) also embedded into the Fortified-Chain 2.0 system to automate patient health monitoring. In the RFSVM module, a random forest (RF) is used to select an optimal set of features from patients data in real-time environment and also support vector machine (SVM) is used to perform the decision making tasks. The proposed Fortified-Chain 2.0 works on a private blockchain-based distributed decentralised storage system (DDSS) that improves the system-level transparency, integrity, and traceability. Fortified-Chain 2.0 outperformed the existing Fortified-Chain in terms of low latency, high throughput, and availability with the help of a mutual authentication method.
Egala et al. (Wed,) studied this question.