Privacy-Preserving Biometric Authentication in Resource-Constrained Environments: A PRISMA Systematic Review of Multimodal and Fuzzy-Vault Methods

As micro, small and medium-sized enterprises (MSMEs) compete with limited resources, lightweight systems are needed to secure their digital assets. Fuzzy vaults (FVs) are useful for protecting secrets and, when applied to biometric systems, provide error-tolerance and privacy to enrolled biometric features. Combining multiple biometric traits also improves performance against attacks like spoofing in multimodal (MM) authentication systems. However, the design of the FV and the biometric-fusion method applied can limit the system’s effectiveness. This study systematically evaluates recent studies on FVs and MM systems and presents an up-to-date review to identify gaps, give directions for future studies, and, ultimately, improve the design of these systems. The research targeting MSMEs was carried out in two parts, with the first search focused on MM systems and the second on FVs, following the PRISMA guidelines. The main findings include the need to optimise the resource intensity of FV systems for the authentication of large numbers of individuals. It also found the need to make the model compatible with other biometric modalities as greater focus is on minutiae features. By reviewing these systems, we aim to foster the development of lightweight MM FV models to provide privacy and security in MSMEs.