A Novel Approach for Improving Dynamic Biometric Authentication and Verification of Human Using Eye Blinking Movement

Saied, Marwa H.; Elshenawy, Ayman; Ezz, Mohamed

doi:10.1007/s11277-020-07601-x

Cited by 13 publications

(7 citation statements)

References 20 publications

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“…Uliyan, Sadeghi and Jalab [126] proposed a method for detecting photo attacks by scanning the lips of the presented Face while the user is required to pronounce a randomly selected sequence of numerals. Saied, Elshenawy and Ezz [127] proposed a method that may be used with any authentication system with a camera, such as a mobile phone, tablet, laptop, access control device, etc. The suggested method takes an authorized person's image and locates the eye region, using CNN to classify open and closed eyes, before capturing face dynamics using a challenge-response authentication mechanism that uses eye blinking.…”

Section: Methods Based On Livenessmentioning

confidence: 99%

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

saleh

Tharwat

Gamalel-Din

2023

Journal of Al-Azhar University Engineering Sector

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The COVID-19 pandemic has changed the lifestyle in global education systems in favor of more reliance on e-learning, which is believed to be a change that will continue. Exams are no exception as they are also moving towards online remote exams where examinees can take their exams at their remote locations. However, it is worth noting that it is still difficult to ensure that the full discipline of the exam session is administered remotely, as is the case for traditional exams that are conducted in the classroom and in the presence of proctors. However, there are many attempts at the commercial and research levels to overcome many of the challenges facing this problem from different angles. Therefore, this survey article attempts to review some of those attempts at both the solutions and technology levels. The article also made some comparisons and evaluations of the techniques and algorithms reviewed as an attempt to assess their weaknesses and strengths in counteracting persistent attempts to circumvent the discipline of the exam system. Hence, this article aims to pave the way for system designers who wish to implement remote exam session management systems by reviewing both commercially available and under-researched technologies. It also aims to introduce researchers to the findings of scientific research so far, while shedding light on open gaps and problems that have not yet been researched.

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Section: Methods Based On Livenessmentioning

confidence: 99%

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

saleh

Tharwat

Gamalel-Din

2023

Journal of Al-Azhar University Engineering Sector

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“…Instead of using a static facial authentication method, Saied et al [4] and Umashankar et al [5] proposed a biometric security system that captures both the face of the individual and patterns of eye blinking. The user blinks their eyes at a specific rhythm, and the system collects information from the image stream.…”

Section: Related Workmentioning

confidence: 99%

Siamese neural network based algorithm for user recognition by their eye blinking

Malinowski,

Saeed

2024

Preprint

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The article proposes a new method for user recognition based on their unique eyelid blinking pattern. Our research aimed to develop a method that is resistant to shoulder surfing and brute force attacks, while also not requiring complex recording devices. Most user authentication methods utilizing eyelid blinking patterns are vulnerable to pattern replication attacks. On the other hand, methods using EEG sometimes require the use of complicated equipment to record the blinking event. In our study, we utilized the publicly available mEBAL database. The temporal eyelid movement patterns extracted from the samples in the database are analyzed by a Siamese neural network. The achieved results of 98.20% accuracy and 0.11 EER unequivocally demonstrate the superiority of the proposed method over other methods using eyelid blinking for user authentication.

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“…While CNN alone can provide state-of-the-art mobile authentication, many studies have paired CNN with other ML algorithms in a hybrid model architecture [78][79][80][81][82]. Study [78] presents a multitask model for mobile authentication via facial attributes.…”

Section: Physiological Biometrics 321 Facial Dynamicsmentioning

confidence: 99%

Deep Learning and Machine Learning, Better Together Than Apart: A Review on Biometrics Mobile Authentication

Kokal

Vanamala

Dave

2023

JCP

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Throughout the past several decades, mobile devices have evolved in capability and popularity at growing rates while improvement in security has fallen behind. As smartphones now hold mass quantities of sensitive information from millions of people around the world, addressing this gap in security is crucial. Recently, researchers have experimented with behavioral and physiological biometrics-based authentication to improve mobile device security. Continuing the previous work in this field, this study identifies popular dynamics in behavioral and physiological smartphone authentication and aims to provide a comprehensive review of their performance with various deep learning and machine learning algorithms. We found that utilizing hybrid schemes with deep learning features and deep learning/machine learning classification can improve authentication performance. Throughout this paper, the benefits, limitations, and recommendations for future work will be discussed.

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A Novel Approach for Improving Dynamic Biometric Authentication and Verification of Human Using Eye Blinking Movement

Cited by 13 publications

References 20 publications

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

Siamese neural network based algorithm for user recognition by their eye blinking

Deep Learning and Machine Learning, Better Together Than Apart: A Review on Biometrics Mobile Authentication

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