Development of Secure Multimodal Biometric System for Person Identification Using Feature Level Fusion: Fingerprint and Iris

Siddiqui, Almas; Telgad, Rupali L.; Lothe, Savita A.; Deshmukh, Prapti D.

doi:10.1007/978-981-13-9184-2_37

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…A minutiae matcher, employing similarity and distance methods, is utilized for fingerprint recognition, whereas iris images are extracted using the wavelet algorithm. The system was assessed on the KVK and an internal datasets, achieving an accuracy of 99.2% with a False Acceptance Rate (FAR) of 0.02% and a FRR of 0.1% (278).…”

Section: Literature Review On Multimodal Fingerprint Biometric Systemsmentioning

confidence: 99%

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

Sumalatha,

Prakasha,

Prabhu

et al. 2024

IEEE Access

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In the contemporary technological landscape, biometrics, encompassing the analysis of biological data, have gained significance. Biometrics is a methodology that utilize unique behavioral, physical, or morphological traits-such as speech, facial features, iris, fingerprint, retina, and signature for individual identification. Biometric technology has been successfully used in forensic science, security, and authorization systems. This review highlights understanding the classification, types of biometric traits and their comparisons, fingerprint recognition stands out as a reliable and widely adopted method due to its simplicity and cost-effectiveness, accuracy and robustness compared to others. Unimodal fingerprint biometric systems safeguard authentication information through the analysis of characteristic sequences and, face challenges such as vulnerability to spoof attacks, inter-class similarity, intra-class variation, non-universality, and noisy data. These challenges are addressed by multimodal fingerprint biometric systems, in which various biometric sources compensate for each other's limitations. The review focuses on the overview of unimodal and multimodal fingerprint biometric systems and the importance of fusion, advancements in data acquisition, preprocessing, feature extraction, matching algorithms, performance metrics, indexing, template protection, and addressing attacks in enhancing system security and reliability. The review paper sheds light on the intricate relationship between these elements, offering valuable insights into the current state and potential evolution of the field. The review paper highlights current challenges and suggests future research directions, emphasizing the necessity for continual advancements in fusion techniques, template protection methods, and novel defense mechanisms to effectively mitigate emerging threats in unimodal and multimodal fingerprint biometric systems.

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Section: Literature Review On Multimodal Fingerprint Biometric Systemsmentioning

confidence: 99%

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

Sumalatha,

Prakasha,

Prabhu

et al. 2024

IEEE Access

View full text Add to dashboard Cite

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Multimodal biometric authentication: A review

Pahuja,

Goel

2024

AIC

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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.

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Development of Secure Multimodal Biometric System for Person Identification Using Feature Level Fusion: Fingerprint and Iris

Cited by 2 publications

References 23 publications

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

Multimodal biometric authentication: A review

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