Enhancing Health Monitoring Security: A Robust Solution with Automated Periodic Re-Authentication
Ovidiu Bica, Dragoș Nicolae NICOLAU, Lidia Băjenaru · 2024
The rapid evolution of telemedicine has necessitated the development of secure and efficient health monitoring systems, particularly for managing chronic diseases. This paper introduces the NeuroPredict platform, focusing on its advanced security mechanisms tailored for continuous and secure health data transmission. The study details an automatic access token updating solution, currently implemented in the NeuroPredict platform, and an experimental Time-Generated Authentication Token (TGAK) designed to enhance security further. Both mechanisms operate autonomously, without requiring user intervention, thereby minimizing the risk of session hijacking and unauthorized access through periodic token refreshes every three hours. Consequently, these mechanisms ensure data flow integrity across Internet of Things (IoT)- enabled medical devices, cloud servers, and data retrieval applications. The proposed security framework represents a substantial advancement in telemedicine by addressing existing vulnerabilities in healthcare data protection and maintaining the integrity of sensitive patient information.