Initial Development of a Learners’ Ratified Acceptance of Multibiometrics Intentions Model (RAMIM)

Levy, Yair; Ramim, Michelle M.

doi:10.28945/84

Cited by 16 publications

(16 citation statements)

References 80 publications

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“…In an attempt to minimise the impersonation threats by employing a non-distractive unimodal biometric solution, Kikuchi et al [29] propose a real-time periodic authentication scheme using biometric handwritingbased samples. Though, behavioural biometrics has been associated with a low error rate in lab settings; further work is required to improve robustness for large scale systems [34]. Moreover, there are limitations imposed on unimodal biometric systems, which can be overcome by multimodal biometrics [46,27,50]…”

Section: Uni-modal Biometric Schemementioning

confidence: 99%

“…Rabuzin et al, [43] asserts that it is necessary to combine several different biometric traits in order to implement absolute security in e-learning systems. Thus, adopting multi-biometrics can increase the reliability of the user security beyond the initial student login process and provide ongoing nonintrusive verification for the duration of test session [14,34]. In literature, few papers exist on the emerging technology of multi-biometrics in elearning security.…”

Section: Bimodal Biometric Schemesmentioning

confidence: 99%

“…Hence, for an online test the student is delayed until the data acquisition process is completed; this presents a window to perpetrate a Type C impersonation. Levy & Ramim, [34] propose a theoretical model which combines a fingerprint and web-camera head geometry scanner. Employing this model depicts a promising solution to minimise the Type B and C impersonation threats.…”

Section: Bimodal Biometric Schemesmentioning

confidence: 99%

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User Security Issues in Summative E-Assessment Security

Apampa¹,

Wills²,

Argles³

2010

IJDS

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Summative electronic assessments embodies enormous advantages such as automated marking, immediate feedback and on-demand tests. User security plays a vital role in summative eassessments, as it ensures that online tests are delivered to the correct students only. Thus, the existing user security model presents a two-layered challenge to the student; whereby responses to "who are you?" and "is it really you?" questions are solicited. Amidst the usefulness of the existing model, summative e-assessments are susceptible to impersonation challenges. In this paper, we classify the user security concerns into Type A, Type B and Type C impersonation types. We suggest that these vulnerabilities can be linked to a weakness in the user security model. Hence, without discarding the existing model we propose a goal-oriented approach to address the user security needs of the eassessment system. Furthermore, a review of the existing solutions depicts insufficient capabilities to minimise all the three types of impersonation challenges. Hence, we propose that an appropriate blend of existing methods will minimise the types of impersonation threats and improve user security in summative e-assessments

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Section: Uni-modal Biometric Schemementioning

confidence: 99%

Section: Bimodal Biometric Schemesmentioning

confidence: 99%

Section: Bimodal Biometric Schemesmentioning

confidence: 99%

See 1 more Smart Citation

User Security Issues in Summative E-Assessment Security

Apampa¹,

Wills²,

Argles³

2010

IJDS

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“…However, studies including Asha & Chellappan [4] and Ross & Jain [5] claim that multimodal biometrics would be a more suitable and robust alternative. A camera supporting head geometry capture and fingerprint scanners could offer solutions for secure user identification for login in addition to continuous authentication [6]. But, this study considers students' acceptance of multimodal biometrics systems for verification throughout an online test, rather than focusing on the practicality, security, applicability and performance of the suggested strategy.…”

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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“…Moreover, they are necessary to confirm users' access in various e-learning course activities [9]. With regard to previous literature, the increased research focused on developing better ways to manage e-examination and e-learning systems.…”

Section: Introductionmentioning

confidence: 99%

A Novel Authentication Scheme for E-assessments Based on Student Behavior over E-learning Platform

Khlifi

El-Sabagh

2017

Int. J. Emerg. Technol. Learn.

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Abstract-E-Learning and distance education have become common choices for academic institutions. Based on advances in information technology systems, educational institutions have enabled the employment of e-learning systems as teaching courses and evaluation students. However, security issues related to e-learning systems have been raised by e-learning environment stakeholders which including faculty members, and students as well as data. In addition, e-learning opponents argue that incapability of e-learning environment to authenticate examination takers is one of the major challenges. E-assessment is an important element of LMS based e-courses, and student authentication is mostly realized as one of the major concerns for e-assessments. For this reason, the main challenge facing the security of e-assessment and the e-learning environment is how to authenticate students because unauthorized persons can access and manage information. In this work, we propose a novel security scheme that contributes in resolving this vital issue by introducing an efficient secure model for supervising online evaluation including e-assessment or e-exam. The scheme addresses this imperative problem by proposing a novel approach that integrates available databases authentication technologies in conjunction with elearning environments for controlling unethical behavior during e-assessment process. Moreover, the proposed scheme considers the continuous random authentication using students' information stored previously in the databases that guarantee identity and authentication. To validate our proposal, and evaluate its performances and effectiveness, an extensive simulation work is conducted over e-learning platform similar to Desire to learn (D2L).Keywords-e-learning platform; e-learning security; presence and identity authentication; e-assessment and e-exam. 62

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Initial Development of a Learners’ Ratified Acceptance of Multibiometrics Intentions Model (RAMIM)

Cited by 16 publications

References 80 publications

User Security Issues in Summative E-Assessment Security

User Security Issues in Summative E-Assessment Security

A Robust e-Invigilation System Employing Multimodal Biometric Authentication

A Novel Authentication Scheme for E-assessments Based on Student Behavior over E-learning Platform

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