Biometric authentication and tracking system for online examination system

Bal, Aditi; Acharya, Arunasish

doi:10.1109/retis.2011.6146869

Cited by 12 publications

(6 citation statements)

References 4 publications

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“…Nobody has the same fingerprint as Even twins with identical D.N.A have different fingerprints; some research records users` fingerprints to be later used for authentication purposes [10,35,36,37,38,39,40,41,42,43,44].…”

Section: Fingerprintmentioning

confidence: 99%

“…Bal, Acharya used the examiner's fingerprint image as a cover image to hide the Personal Authentication Number (P.A. N) [41]. The authors in [86,87] Recorded the facial image and an image of the fingerprint.…”

Section: Multi-factorsmentioning

confidence: 99%

“…In [95,96], the authors described a study that built a combination of a student's Keystroke and stylometry template. Bal, Acharya suggested using a mix of steganography and students` fingerprints [41]. This template was previously used in other domains, such as online voting [97] and online buying [98].…”

Section: Multi-factorsmentioning

confidence: 99%

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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: Fingerprintmentioning

confidence: 99%

Section: Multi-factorsmentioning

confidence: 99%

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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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“…Iris is a flexible and colored tissue that controls the pupil [40]. Iris recognition is a way to control student impersonation another in online exam [4]. [19] Used Iris recognition method for mobile phone to prevent unauthorized access to mobile phone by using mobile camera for recognition.…”

Section: Related Workmentioning

confidence: 99%

A proposed Iris Recognition Model for Authentication in Mobile Exams

Shdaifat

Obeidallah

Ghazal

et al. 2020

Int. J. Emerg. Technol. Learn.

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Mobile learning is an extended version of e-learning. The revolution of handheld devices had encouraged design courses to be compatible with different mobiles versions, brands and platforms. Mobile exams need more attention to strengthen mobile learning certificates. A major issue with mobile exam is student authentication and identification before and during exam session. With no presence of proctor, more techniques are available to ensure student identification. In this paper, we proposed a model that uses a traditional username and password in addition to the biometric iris recognition technique to verify student identity before and during mobile exams.

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“…Biometric approaches are currently being adopted in this area with many researchers suggesting unimodal biometric solutions (e.g. iris recognition [2], or keystroke recognition [3]). However, studies including Asha & Chellappan [4] and Ross & Jain [5] claim that multimodal biometrics would be a more suitable and robust alternative.…”

Section: Related Workmentioning

confidence: 99%

A Robust e-Invigilation System Employing Multimodal Biometric Authentication

Ketab¹,

Clarke²,

Dowland³

2017

IJIET

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Abstract-The significant growth in users of e-learning technologies and their use in courses has given rise to a major concern over protecting them from misuse; a significant concern is that of the potential for cheating or illicit assistance during online examinations. This paper presents the development of robust, flexible, transparent and continuous authentication mechanism for e-assessments. To monitor the exam taker and ensure that only the legitimate student is taking the exam, the system offers a continuous user identification employing multimodal biometrics; a security layer using an eye tracker to record the student's eye movement; and, speech recognition to detect inappropriate communication. The focus of this paper in particular is the development and evaluation of 3D facial authentication. An experiment has been conducted to investigate the ability of the proposed platform to detect any cheating attempts. During the experiment, participants' biometric data, eye movement, and head movements have been collected using custom software. The 3D camera also captured the session using a built-in microphone and the system recognized speech (employing a speech recognition algorithm). 51 participants participated in this experiment. The FRR of all legitimate participants was 0 and 0.0063 in 2D and 3D facial recognition modes respectively. Furthermore, three participants were tasked with a series of eight scenarios that map to typical misuse. The results of the FAR and FRR of five of these threat scenarios in both 2D and 3D mode were 0 with two cases exhibiting an FAR of 0.11 and 0.076 in the 2D mode.

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Biometric authentication and tracking system for online examination system

Cited by 12 publications

References 4 publications

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

A proposed Iris Recognition Model for Authentication in Mobile Exams

A Robust e-Invigilation System Employing Multimodal Biometric Authentication

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