Blockchain Approach for Healthcare Using Fog Topology and Lightweight Consensus - Aya Laouamri; Sarra Cherbal; Yacine Mosbah; Chahrazed Benrebbouh; Kamir Kharoubi (Acta Informatica Pragensia)
Background: The internet of things (IoT) has transformed healthcare by integrating various devices and systems, fostering innovation in data management and operational efficiency. However, ensuring data integrity, security and trust within IoT networks remains a pressing challenge, particularly in critical sectors such as healthcare.Objective: This study aims to explore the integration of blockchain technology with IoT systems, focusing on addressing scalability and real-time applicability issues in healthcare data management. By proposing novel solutions, the research seeks to enhance the security and reliability of IoT systems in healthcare environments.Methods: The proposed framework incorporates a lightweight raft-based consensus protocol and enhanced cryptographic measures, such as Schnorr signatures and hashes, to address existing limitations in scalability and latency. The architecture and algorithms for signature generation, encryption, emergency state actions and consensus are developed and evaluated through extensive simulations using the NS3 toolkit.Results: The simulation results validate the effectiveness of the proposed approach in improving healthcare IoT systems. The findings demonstrate enhancements in energy efficiency, throughput and network usage, establishing the potential of the framework for revolutionizing healthcare data management by providing secure, scalable and efficient solutions.Conclusion: The study contributes to advancing secure and reliable decentralized data management systems for IoT in healthcare by making use of blockchain technology. The proposed architecture addresses critical challenges and offers practical benefits such as resource efficiency and system stability. While promising, the framework requires real-world testing and further optimization to overcome potential scalability bottlenecks in large-scale healthcare deployments.