A Secure and Privacy-Preserving ABAC-Driven Remote Patient Monitoring System Using Blockchain Technology

Abstract

Rapid development in remote monitoring healthcare systems has led to the need for secure, efficient, and privacy-preserving methods for handling sensitive patient data. Centralized healthcare systems usually experience problems such as unauthorized access, lack of transparency, single point of failure, and difficulty with auditing, among others, that may compromise both patients’ data privacy and security. In order to solve this, the proposed system offers decentralized, transparent, and secure data management in healthcare using blockchain technology and the ABAC approach. A Hyperledger framework is chosen to build the network, and the performance of the network is evaluated using Hyperledger Caliper at fixed workloads of 1000 transactions by varying the transaction send rate in bunches of 25, 50, 100, 150, 200, 500, 1000 and 1500. Throughput, latency, memory consumption and reliability are widely used metrics that are investigated in performance evaluation of the proposed model to determine whether the framework can operate effectively and scale successfully under specific conditions. According to the experimental data, the system reached a 100% transaction success rate without any failures in the process of transferring transactions, even in cases of high send rates, such as 1000 transactions at a transaction send rate of 1500. Throughput rose gradually with increasing load of transactions from 24.6 transactions per second up to 798.1 transactions per second. Even though latency and commit time grew with an increase in workload, these parameters still remained within permissible limits. Therefore, the framework demonstrates acceptable throughput, good latency and ABAC policy enforcement for the synthetic workload configurations. The test results provide a robust architectural baseline for a remote patient monitoring model.