Investigating the Role of Multibiometric Authentication in Professional Certification E-exams

E-learning has grown to such an extent that paper-based testing is being replaced by computer-based testing also known as e-exams. Because these e-exams can be delivered outside of the traditional proctored environment, additional authentication measures must be employed in order to offer similar authentication assurance as found in proctored, Paper-Based Testing (PBT). In this study, we extended the body of knowledge in e-learning research by comparing e-exam scores and durations of three separate groups of e-exam takers using different authentication methods: Online Using Username/Password (OLUP), In-Testing Proctored Center (ITPC), and Online Proctored with Multibiometrics (OPMB). The aim was to better understand the role as well as the possible effect of continuous and dynamic multibiometric authentication on professional certification e-exam scores and durations. Our results indicated that group affiliation, i.e. type of authentication methods, had no significant effect on differences among e-exam scores and durations. While there was a clear path of increased mean e-exam score as authentication method was relaxed, it was evident from the analysis that these were not statistically significant,probably due to the limited sample size. Age was found to have a significant effect on e-exam scores where younger participants were found to have higher e-exam scores and lower e-exam durations than older participants. Gender was not found to have a significant effect on e-exam scores nor durations. This study’s results can help organizations better understand the role, possible effect, and potential application of continuous and dynamic multibiometric authentication as a justifiable approach when compared with the more common authentication approach ofUser Identifier (UID) and password, both in professional certification e-exams as well as in an online environment

Selected Computing Research Papers Volume 1 June 2012

An Evaluation of Anti-phishing Solutions (Arinze Bona Umeaku) ..................................... 1 A Detailed Analysis of Current Biometric Research Aimed at Improving Online Authentication Systems (Daniel Brown) .............................................................................. 7 An Evaluation of Current Intrusion Detection Systems Research (Gavin Alexander Burns) .................................................................................................... 13 An Analysis of Current Research on Quantum Key Distribution (Mark Lorraine) ............ 19 A Critical Review of Current Distributed Denial of Service Prevention Methodologies (Paul Mains) ............................................................................................... 29 An Evaluation of Current Computing Methodologies Aimed at Improving the Prevention of SQL Injection Attacks in Web Based Applications (Niall Marsh) .............. 39 An Evaluation of Proposals to Detect Cheating in Multiplayer Online Games (Bradley Peacock) ............................................................................................................... 45 An Empirical Study of Security Techniques Used In Online Banking (Rajinder D G Singh) .......................................................................................................... 51 A Critical Study on Proposed Firewall Implementation Methods in Modern Networks (Loghin Tivig) .................................................................................................... 5

Algoritmos de deteção de comportamento de indivíduos com autismo: análise comparativa

A elevada prevalência de doenças relacionadas com o autismo e a necessidade de descoberta desta patologia de difícil diagnóstico e convivência, levou a que seja imprescindível o desenvolvimento de mecanismos de deteção e avaliação da atividade de pacientes. Esta tese tem como principal objetivo colmatar estas necessidades. Os algoritmos testados são direcionados à melhoria da monitorização de doentes com autismo e com necessidades especiais. Estes têm como principal objetivo a utilização numa casa direcionada à terapia e convivência de doentes com autismo. Através destas técnicas será possível melhorar a qualidade de vida dos pacientes e responder a emergências que possam surgir. Os dados provenientes de sensores como a câmara Kinect vão servir para detetar movimentos estereotipados característicos de doenças do espectro do autismo. Assim podem ser monitorizadas atividades anormais e por consequência antecipar algum tipo de anomalia. Por outro lado será possível avaliar a evolução do doente ao longo de uma série de tratamentos e terapias. Neste projeto foi avaliada a performance de vários algoritmos de deteção e avaliação de movimentos adaptados às necessidades presentes. Foi também conduzido um estudo sobre as tecnologias de reconhecimento de expressões faciais e identificação de pessoas pela face. Os algoritmos foram testados com movimentos de pessoas sem doenças do espetro do autismo devido à maior facilidade de trabalhar neste contexto. Posteriormente transpõem-se as tecnologias para onde forem necessárias

Group-specific face verification using soft biometrics

Soft biometrics have been recently proposed for improving the verification performance of biometric recognition systems. Examples of soft biometrics are skin. eyes, hair colour, height, and ethnicity. Some of them are often cheaper than "hard", standard biometrics (e.g., face and fingerprints) to extract. They exhibit a low discriminant power for recognizing persons, but can add some evidences about the personal identity, and can be useful for a particular set of users. in particular, it is possible to argue that users with a certain high discriminant soft biometric can be better recognized. Identifying such users could be useful in exploiting soft biometrics at the best, as deriving an appropriate methodology for embedding soft-biometric information into the score computed by the main biometric. In this paper, we propose a group-specific algorithm to exploit soft-biometric information in a biometric verification system. Our proposal is exemplified using hair colour and ethnicity as soft biometrics and face as biometric. Hair colour and information about ethnicity can be easily extracted from face images, and used only for a small number of users with highly discriminant hair colour or ethnicity. We show by experiments that for those users, hair colour or ethnicity strongly contributes to reduce the false rejection rate without a significant impact on the false acceptance rate, whilst the performance does not change for other users. (C) 2009 Elsevier Ltd. All rights reserved