Automated and Secure Login in ALERTAR, a Resilient Cloud–Fog–Edge mHealth System for Hospital Environments

Abstract

ALERTAR system aims to assist healthcare providers in identifying early clinical deterioration in hospitalized patients on general wards. Its cloud-fog-edge architecture uses only mobile devices at the fog and edge levels to simplify its operability. As a critical healthcare system, it is of utmost importance to provide resilience across multiple layers of the architecture. To tolerate faults, the system can dynamically migrate devices between the fog and edge layers. This work focuses on describing an automated and secure login method for this system. To reduce user intervention and simplify system use, the login process has been automated by storing session credentials and utilizing a fog-level device discovery process. The design of the login mechanism is aligned with the strict security requirements of the system, considering the sensitivity of the data and the criticality of the service. This is a work in progress so performance evaluations are still pending.