Next-Gen Healthcare: Blockchain-Fuelled Federated Learning for IoMT Security

Abstract

The Internet of Medical Things (IoMT) is revolutionising the healthcare landscape by seamlessly integrating medical devices, sensors, and healthcare information systems. This interconnected network of devices is designed to improve patient outcomes, enhance healthcare delivery, and streamline medical processes. However, as IoMT continues to evolve, it introduces new challenges related to data security, privacy, and interoperability. Blockchain technology has emerged as a promising solution to address these challenges, offering a decentralised and secure framework for managing health-related data in IoMT applications. This research aims to implement a blockchain-enabled network within a Federated Learning-based Internet of Medical Things (IoMT) environment. The proposed framework features a centralized server hosting a global machine learning model. IoMT devices operate with local models that run concurrently with the global model, incorporating device-specific data. Simulations and comparisons have been conducted on the predominant consensus models, namely Proof of Stake and Proof of Work. These ongoing initiatives aspire to play a role in enhancing the security and privacy aspects of the latest developments in the Internet of Medical Things.