Enhancing healthcare consensus mechanism - A reputation integrated variant of PBFT (BR-PBFT)

In the rapidly evolving healthcare landscape, adopting blockchain technology requires an optimal consensus mechanism to ensure security, efficiency, reliability, and scalability. This paper examines various consensus methods, including PoW (Proof of Work), PBFT(Practical Byzantine Fault Tolerance), its variants, and node reputation management techniques such as the Beta Reputation Model and EigenTrust score, to determine the most suitable approach for healthcare applications. Among the analyzed algorithms, SBFT (Scalable Byzantine Fault Tolerance) emerges as a strong contender due to its fault tolerance and effectiveness in large-scale environments. Building on these insights, we introduce a light weight consensus BR-PBFT(Beta Reputation integreted PBFT), a novel PBFT variant that integrates a beta reputation scoring system and Verifiable random functions (VRF) for more reliable node selection. This enhancement strengthens trust in the network and mitigates malicious behavior by dynamically adjusting node selection and consensus processes based on reputation metrics. Preliminary evaluations indicate that our PBFT variant built on reputation significantly improves CPU consumption and memory efficiency, offering improved reliability, scalability, and performance. These advancements position BR-PBFT as a promising state-of-the-art solution for secure and efficient blockchain implementations in healthcare.