Enhancing biometric system selection: A hybrid AHP-neutrosophic fuzzy TOPSIS approach

A biometric system is essential in improving security and authentication processes across a variety of fields. Due to multiple criteria and alternatives, selecting the most suitable biometric system is a complex decision. We employ a hybrid approach in this study, combining the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Analytic Hierarchical Process (AHP). Biometric technologies are ranked using the TOPSIS method according to the relative weights that AHP determines. By applying the neutrosophic set theory, this approach effectively handles the ambiguity and vagueness inherent in decision-making. Fingerprint, face, Iris, Voice, Hand Veins, Hand geometry and signature are the seven biometric technologies that are incorporated in the framework. Seven essential characteristics are accuracy, security, acceptability, speed and efficiency, ease of collection, universality, distinctiveness used to evaluate these technologies. The model seeks to determine which biometric technology is best suited for a particular application or situation by taking these factors into account. This technique may be applied in other domains in the future.