Linking Biometric Voice Identity with Self-monitoring Health Data as a Temporal-spatial Event Stored in a Mobile Device

Sy, B.

The goal of this research is to investigate a biometric solution that links biometric personal identity to selfmonitoring data, with time and location information, as a temporal-spatial event in a personal health record stored in a mobile device. The proposed biometric solution is based on a secure computation technology that reconstructs a cryptographic key for (un)locking personal health record in real time when a verification sample is sufficiently similar to the enrollment sample - whereas the verification process is based on a secure twoparty security computation that compares the enrollment and verification samples without either party sharing the data with each other, nor relying on a trusted third party. The contribution of this research is to demonstrate the practical feasibility of the approach in a resource constrained mobile computing environment. The significance of this research is its potential application for enabling a safe bubble space for social interaction among individuals who have self-monitoring data showing lack of Covid-19 symptoms at a specific time and location.