Improving Data Security and Scalability in Healthcare System using Blockchain Technology

The wearable tech revolution and the proliferation of Internet of Things (IoT) gadgets have created exciting new opportunities for remote patient monitoring. Healthcare providers are increasingly utilizing wearable technologies to expedite the process of diagnosis and treatment. The healthcare and research fields have been substantially impacted by emerging technologies. On the other hand, there are legitimate worries regarding the security of data transfers and transaction recording upon using these technologies. Healthcare departments need easy data interchange for interoperability. Protecting data security and integrity is crucial when exchanging information with authorized parties. In many existing solutions, patients’ sensitive data is collected and stored in smart healthcare systems. Scalability, breach or unauthorized access to this data can compromise privacy. The adoption of blockchain technology is one way to safeguard patient privacy in healthcare. Also, by facilitating the safe and secure exchange of data, blockchain technology is revolutionizing the healthcare industry by making traditional methods of diagnosis and treatment more reliable. However, blockchain has serious problems with its highly limited scalability. This article suggests a new method “SHORTBLOCKS” depending on blockchain technology for the safe administration and analysis of data. To circumvent the security-scalability issue and achieve high throughput, this study employs the newly introduced protocol “SHORTBLOCKS”, which extends blockchain concept to a direct acyclic graph of blocks. The proposed system uses both a private and a public blockchain that are created on the new protocol. In order to analyze patient health data, a system using smart contracts and a private blockchain is built. The system logs the occurrence to the public blockchain in the case that the smart contract raises an alarm due to an unusual reading. This will fix the scalability issue with initial blockchain as well as the security and privacy issues involved in remote patient monitoring. Simulation results shows the performance of the proposed system by comparing with existing solutions, SPECTRE protocol and GHOSTDAG protocol.