A Video-Based Biometric Authentication for e-Learning Web Applications

Penteado, Bruno Elias; Marana, Aparecido Nilceu

doi:10.1007/978-3-642-01347-8_64

Cited by 12 publications

(8 citation statements)

References 12 publications

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“…Authentication controls have three common factors that challenge what: a user knows (a password), a user has (a token), or a user is (a biometric) (Furnell, 2007). Although, a number of differing solutions have been proposed to address this prevailing issue by using authentication controls with a wide variation of strength, there is a lack of consistency in what level of authentication strength is suitable (Jalal & Zeb, 2008;Penteado & Marana, 2009). Authentication strength is measured by the combinations of the number and the type of authentication factors used to identify a remote system user (O'Gorman, 2003).…”

Section: Item Descriptionmentioning

confidence: 99%

An empirical study of authentication methods to secure e-learning system activities against impersonation fraud

Beaudin

Levy

Parrish

et al. 2016

OJAKM

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The demand for e-learning systems in both academic and non-academic organizations has increased the need to improve security against impersonation fraud. Although there are a number of studies focused on securing Web-based systems from Information Systems (IS) misuse, research has recognized the importance of identifying suitable levels of authenticating strength for various activities. In e-learning systems, it is evident that due to the variation in authentication strength among controls, a ‘one size fits all’ solution is not suitable for securing diverse e-learning activities against impersonation fraud. The focus of this exploratory study was to investigate what levels of authentication strength users perceive to be most suitable for activities in e-learning systems against impersonation fraud and aimed to assess if the ‘one size fits all’ approach that is mainly used is valid when it comes to securing e-learning activities from impersonation fraud. A sample of 1,070 e-learners was analyzed using descriptive statistics and exploratory factor analysis to uncover suitable levels of authentication strength to secure elearning activities against impersonation fraud. The findings determined that there is a specific set of e-learning activities that have high potential for impersonation and need a moderate to high level of authentication strength to reduce the threat.

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Section: Item Descriptionmentioning

confidence: 99%

An empirical study of authentication methods to secure e-learning system activities against impersonation fraud

Beaudin

Levy

Parrish

et al. 2016

OJAKM

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“…In addition, secure real-time user authentication and access right management solutions are being actively researched and deployed in both universities and corporate settings (Deutschmann, Nordstrom, & Nilsson, 2013;Penteado & Marana, 2009;Zhou & Bhanu, 2007). In response to these demands, researchers are actively seeking new communication and collaboration technologies, which will reduce meeting attendees' enrollment time and provide the meeting organizer with the tools for efficient real-time attendance tracking and access resource management.…”

Section: Biometric-based User Authentication and Activity Level Detecmentioning

confidence: 99%

“…Traditional approaches to the problem involve the use of IDs, smart cards, and user password/logon, coupled with user identity management solutions, all of which require a significant amount of time and additional resources (Jeon, Kim, & Kim, 2011;Kumar, 2010). Rapid development of biometric technologies opened the door to a new class of fast and reliable identity management solutions and changed the research landscape (Down & Sands, 2004;Penteado & Marana, 2009;Yanushkevich, Gavrilova, Wang, & Srihari, 2007). A biometric system can be defined as a patternrecognition system that can recognize individuals based on the characteristics of their physiology or behavior (Prabhakar, Pankanti, & Jain, 2003).…”

Section: Biometric-based User Authentication and Activity Level Detecmentioning

confidence: 99%

Transparency in Social Media

Matei¹,

Russell²,

Bertino³

2015

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A series of authored and edited monographs that utilize quantitative and computational methods to model, analyze and interpret large-scale social phenomena. Titles within the series contain methods and practices that test and develop theories of complex social processes through bottom-up modeling of social interactions. Of particular interest is the study of the co-evolution of modern communication technology and social behavior and norms, in connection with emerging issues such as trust, risk, security and privacy in novel socio-technical environments.Computational Social Sciences is explicitly transdisciplinary: quantitative methods from fields such as dynamical systems, artificial intelligence, network theory, agentbased modeling, and statistical mechanics are invoked and combined with state-ofthe-art mining and analysis of large data sets to help us understand social agents, their interactions on and offline, and the effect of these interactions at the macro level. Topics include, but are not limited to social networks and media, dynamics of opinions, cultures and conflicts, socio-technical co-evolution and social psychology. Computational Social Sciences will also publish monographs and selected edited contributions from specialized conferences and workshops specifically aimed at communicating new findings to a large transdisciplinary audience. A fundamental goal of the series is to provide a single forum within which commonalities and differences in the workings of this field may be discerned, hence leading to deeper insight and understanding. Series EditorsMore information about this series at

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“…Hence, the authors propose an authentication system that exploits multi-biometrics to support various services in eLearning where user authentication is required. The use of webcam face images to authenticate the presence of users during on-line courses is addressed by the work in [24]. Also, the authors in [25] introduce a biometric scheme for providing continuous user authentication in e-examination through keystroke dynamics.…”

Section: Related Orkmentioning

confidence: 99%

“…So, they require special effort to become crossoperable and interoperable. On the other hand, most of the biometric solutions proposed so far either require special equipment to be deployed in certain places [24], or impose the use of expensive equipment [22], [26], [27]. A major problem of biometrics authentication (like Keystroke [25] and mouse clicking) is that it is not free from errors and false recognition rate can be very high.…”

Section: Related Orkmentioning

confidence: 99%

A Competent Post-Authentication and Non-Repudiation Biometric-based Scheme for M-Learning

Kambourakis¹,

Damopoulos²

2013

Artificial Intelligence and Applications / 794: Modelling, Identification and Control / 795: Parallel and Distributed Computing

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As mobile learning (mLearning) gains momentum, so does the worry of the parties involved to mLearning activities regarding the security and privacy level of the underlying systems and practices. Indeed, the basically spontaneous nature of mLearning and the variety of out-of-control devices that are used for supporting its activities, makes it prone to a plethora of attacks such as masquerading and manin-the-middle. Thus, the provision of some sort of postauthentication and non-repudiation service in an effort to deter and repel ill-motivated activities may be of particular value in such realms. Compelled by this fact, in this paper, we introduce a dynamic signature-based biometric scheme to enable the offering of both of the aforementioned services in mLearning domains. We argue that our solution is both practical and lightweight. Its feasibility is also demonstrated through the use of machine learning techniques.

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A Video-Based Biometric Authentication for e-Learning Web Applications

Cited by 12 publications

References 12 publications

An empirical study of authentication methods to secure e-learning system activities against impersonation fraud

An empirical study of authentication methods to secure e-learning system activities against impersonation fraud

Transparency in Social Media

A Competent Post-Authentication and Non-Repudiation Biometric-based Scheme for M-Learning

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