Biometric-Based Authentication in Internet of Things (IoT): A Review

Singh, Vijender; Kant, Chander

doi:10.1007/978-981-19-0619-0_27

Cited by 5 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Certain researchers have implemented a unimodal biometric technique as a face or voice-only biometric technology. Multiple biometric modalities are utilized in multimodal biometrics to ensure system quality and prevent biometric systems from having a single point of failure [26]. The biometric protocol gaps between unimodal and multimodal biometrics for identity verification in education are primarily concerned with the cost and accuracy of identity verification [27], [28].…”

Section: Figure 1 Traditional Approach Of Examination Takers' Identif...mentioning

confidence: 99%

See 1 more Smart Citation

IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach

2023

View full text Add to dashboard Cite

Traditional identity verification of students based on the human proctoring approach can cause a scam identity verification and ineffective processing time, particularly among vast groups of students. Most student identification cards are outdated personal information. Several biometric recognition approaches have been proposed and can be adopted to strengthen students' identity verification. Most educational adoption technology struggles with evaluation and validation techniques to ensure that biometric recognition systems are unquestionably suitable for utilization and implementation to fulfill student identity verification. This study presents the internet of things to develop flexible biometric recognition systems and an approach to assess the quality of biometric systems for educational use by investigating the effectiveness of identity verification of various biometric recognition technologies compared to the traditional verification method. The unimodal, multimodal, and semi-multimodal biometric technologies were tested using the developed internet of things-base biometric recognition systems examined by applying the proposed quality metrics of scoring factors based on accuracy, error rate, processing time, and cost. Hundreds of undergraduate exam takers were a sample group. Key findings indicate that the designed and presented systems suitably attain identity verification of exam students using a unimodal biometric. A unimodal face biometric system promises excellent support. A unimodal fingerprint biometric system assures the second excellent aid for student identity verification. However, multimodal and semi-multimodal biometric systems provide better accuracy with few handling times and higher costs. This study contributes significantly to the knowledge of utilizing biometric recognition for identity verification in smart educational use.

show abstract

Section: Figure 1 Traditional Approach Of Examination Takers' Identif...mentioning

confidence: 99%

“…Biometric authentications are popular, more reliable, and user-friendly than conventional methods. The previous research has discussed IoT issues and challenges regarding biometric security and application, including where biometrics can be integrated into IoT infrastructure [26], [51], [57].…”

Section: E Biometric Technology On Internet Of Things Platformmentioning

confidence: 99%

IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach

2023

View full text Add to dashboard Cite

show abstract

“…In our daily lives, we increasingly use smart objects such as smartphones, smartwatches, smart cards, etc., as a physical gateway to our digital services. To meet security trends, biometric is often applied for user authentication (Liu et al, 2022 ; Singh and Kant, 2022 ) to replace passwords. Digital fingerprint is a well-known morphological biometric modality (Maltoni et al, 2009 ) with many advantages for such embedded devices.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of minutiae selection methods for digital fingerprints

et al. 2023

View full text Add to dashboard Cite

Biometric systems are more and more used for many applications (physical access control, e-payment, etc.). Digital fingerprint is an interesting biometric modality as it can easily be used for embedded systems (smartcard, smartphone, and smartwatch). A fingerprint template is composed of a set of minutiae used for their comparison. In embedded systems, a secure element is in general used to store and compare fingerprint templates to meet security and privacy requirements. Nevertheless, it is necessary to select a subset of minutiae from a template due to storage and computation constraints. In this study, we present, a comparative study of the main minutiae selection methods from the literature. The considered methods require no further information like the raw image. Experimental results show their relative performance when using different matching algorithms and datasets. We identified that some methods can be used within different contexts (enrollment or verification) with minimal degradation of performance.

show abstract