Multi-Modalities Biometric Encryption to Secure Personal Data Offloading to the Cloud

Data security has remained a paramount concern for the last decade. Data security saw the introduction of biometric-based security methods. Single biometric-based security methods worked well, but the issue of biometric variability impacted these systems performance. On the other hand, multimodal biometric security systems are less affected by biometric variability than single biometric-based systems. Single biometric-based schemes have the inherent issue of a single point of failure. Multimodalities not only resolve the issue of single-point failure but also increase the reliability of the security scheme. Furthermore, the use of multimodalities enables us to use fixed and cancellable biometrics together to get the security benefits of both types of biometrics. Fixed biometrics offer high reliability; on the other hand, cancellable biometric modalities create a scope to generate different templates from the same biometric, which in terms allows to change the key in case the original key gets compromised. In this paper, we propose a novel approach for securing personal data using an encryption key derived using multi-modalities, which can be used to secure crucial personal data offloading to the cloud or storing at a local data center. Suggested approach has achieved Genuine Acceptance Rate (GAR) of 94% and Genuine Rejection Rate (GRR) of 96% which is better than the single biometric encryption.