Adoption of Bloom Filter and Firebase Framework to Enhance Authentication Time for Healthcare Systems Based on Blockchain Technology

Abstract

Healthcare offers several advantages for actual-time smart healthcare. security concerns are growing due to its constrained computing power, storage capacity, and self-defense capabilities. The tamper-resistant decentralized architecture of more recent blockchain-based authentication solutions gives them significant security features, but they come with a high resource cost because they need a lot of processing power, additional storage, and lengthy authentication processes. Therefore, these challenges offer impediments to achieving the optimal degrees of temporal efficiency and scalability, which are critical for the effective operation of large-scale, time-sensitive IoHT systems. Our work provides an authentication solution specifically created for healthcare systems to address these issues. We work in three phases: initializing, registering, logging in, and authenticating. The suggested system combines blockchain technology, Firebase Framework, Bloom Filter, Multi-Factor authentication, and other elements to improve security and efficiency at the same time. We use the Python programming language to simulate the work, and our findings indicate that the Bloom filter decreases the amount of time it takes to determine whether a person is in the system compared to the previous way. Moreover, using Firebase may reduce transaction numbers by up to 73%. Using the Scyther tool, a security analysis of the proposed scheme proved that the suggested plan is safe from possible threats and maintains the IoHT system's scalability