This review highlights optimal biometric traits and fusion strategies for improved robustness in multi-biometric authentication systems.
Abstract Multi-biometric authentication is increasingly favored over single-biometric systems due to its enhanced robustness, performance, and security. Over the years, extensive research has been conducted to analyze and combine various physical and behavioral biometric traits-from head to toe-to improve authentication methods. Despite significant advancements, the quest for optimal biometric combinations that offer both robustness and efficiency, continues to engage biometric researchers. This study presents a structured review of the literature on multi-biometric authen-tication. It investigates the search for effective biometric authentication, with a particular focus on the selection of optimal biometric traits, trending features, and fusion strategies. Furthermore , it compiles a comprehensive list of key methodologies contributed by researchers across different timeframes and sources, ensuring a balanced and thorough analysis. List of popular datasets with important characteristics is also prepared. Key findings are presented in a detailed yet accessible manner through graphs, tables, and equations. The review concludes with recommendations on the most suitable biometric traits and effective methodologies for multi-biometric authentication. Notably, the study highlights the face–iris–periocular trio as the most robust and efficient combination for integration into multi-biometric authentication systems. These insights offer clear direction for advancing research in multi-biometric authentication.
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Prasad et al. (2025) studied this question.
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