Automated Remote Patient Monitoring: Data Sharing and Privacy Using Blockchain (1811.03417v1)

Abstract: The revolution of Internet of Things (IoT) devices and wearable technology has opened up great possibilities in remote patient monitoring. To streamline the diagnosis and treatment process, healthcare professionals are now adopting the wearable technology. However, these technologies also pose grave privacy risks and security concerns about the transfer and the logging of data transactions. One solution to protect privacy in healthcare is the use of blockchain technology. However, one of the primary problems with blockchain is its highly limited scalability. In this work here, we propose the utilization of a blockchain based protocol to provide secure management and analysis of data. In this paper we use recently introduced PoW based protocol GHOSTDAG, that generalizes Satoshi's blockchain to a direct acyclic graph of blocks (blockDAG) and provides high throughput while also avoiding the security-scalability problem. We use two blockchains based on the original GHOSTDAG protocol, one that is private and one that is public. Using a private blockchain, we create a system where we use smart contracts to analyze patient health data. If the smart contract for any reason issues an alert for an abnormal reading then the system makes the record of that event to the public blockchain. This would resolve the privacy and security vulnerabilities associated with remote patient monitoring and also the limited scalability problem of Satoshi's original blockchain.