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Article type: Review Article
Authors: Pahuja, Swimpya; * | Goel, Navdeepb
Affiliations: [a] Department of Computer Science & Engineering, Punjabi University, Patiala-147002, Punjab, India | [b] Yadavindra Department of Engineering, Punjabi University, Guru Kashi Campus, Damdama Sahib, Talwandi Sabo-151302, Punjab, India
Correspondence: [*] Corresponding author. E-mail: [email protected].
Abstract: Critical applications ranging from sensitive military data to restricted area access demand selective user authentication. The prevalent methods of tokens, passwords, and other commonly used techniques proved deficient as they can be easily stolen, lost, or broken to gain illegitimate access, leading to data spillage. Since data safety against tricksters is a significant issue nowadays, biometrics is one of the unique human characteristic-based techniques that may give better solutions in this regard. The technique entails biometric authentication of users based on an individual’s inimitable physiological or behavioral characteristics to provide access to a specific application or data. This paper provides a detailed description of authentication and its approaches, focusing on biometric-based authentication methods, the primary challenges they encounter, and how they have been addressed. The tabular view shows the benefits and downsides of various multimodal biometric systems, and open research challenges. To put it another way, this article lays out a roadmap for the emergence of multimodal biometric-based authentication, covering both the challenges and the solutions that have been proposed. Further, the urge to develop various multi-trait-based methods for secure authentication and data privacy is focused. Lastly, some multimodal biometric systems comprising fingerprint and iris modalities have been compared based on False Accept Rate (FAR), False Reject Rate (FRR), and accuracy to find the best secure model with easy accessibility.
Keywords: Authentication, multimodal biometrics, identification, biometrics
DOI: 10.3233/AIC-220247
Journal: AI Communications, vol. 37, no. 4, pp. 525-547, 2024
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