Ensuring Health Monitoring with Smart Glucometer using Ring Learning with Errors (RLWE) and Blockchain Integration for Enhanced Security

Abstract

Worldwide diabetes prevalence is rising, which emphasizes the necessity for safe health monitoring methods. The present study investigates the potential of implementing Ring Learning With Errors (RLWE) encryption in a smart glucometer to augment security and privacy in the context of diabetes care. Sensitive health data is encrypted and stored securely with RLWE, a lattice-based cryptography method. The Ethereum blockchain is used by the smart glucometer to provide decentralized and unchangeable data management, and RLWE encryption is included for data security. Ethereum smart contracts offer strong security features by ensuring data integrity and access management. Performance criteria, such as memory utilization and encryption or decryption times, evaluate the usefulness of RLWE in real-world medical equipment. The study highlights RLWE’s effectiveness in preventing unauthorized access to sensitive data and shows notable developments in secure health information systems. The potential of blockchain technology and RLWE efficiency over LWE to improve healthcare data security and the same is highlighted by the results obtained through the various calculations done. The study advances patient care and data security in healthcare settings by promoting safe and reliable medical IoT devices through the use of advanced cryptographic algorithms and decentralized data management.