Soft Biometrical Students Identification Method for e-Learning
bf The paper describes a soft biometrical characteristics based approach to the students’ identification process to be used mainly for e-learning environments. This approach is designed to increase security of the examination process from the involved attendees’ identification point of view and should improve the overall security in relatively weakly protected e-learning systems. The approach is called "soft" as doesn’t require any special systems to be used other than e-learning pages embedded software. The paper discusses how the approach can be applied and what kind methods should be used together with the proposed one to produce a complete identification system for e-learning.
KeywordsVerification System Student Identification Biometrical Measure Examination Process Pattern Database
Unable to display preview. Download preview PDF.
- E. González-Agulla, E. Argones-Rúa, C. García-Mateo, and ó W. M. Flórez, “Development and Implementation of a Biometric Verification System for E-learning Platforms”, EDUTECH, Computer-Aided Design Meets Computer-Aided Learning, IFIP 18th World Computer Congress, 2004, pp. 155-164.Google Scholar
- O. Guven, S. Akyokus, M. Uysal, and A. Guven, “Enhanced password authentication through keystroke typing characteristics”, Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications, 2007, pp. 317-322.Google Scholar
- J. Illonen, “Keystroke dynamics”, In Advanced Topics in Information Processing Lectures, 2003.Google Scholar
- R. Gaines, W. Lisowski, S. Press, and N. Shapiro, “Authentication by Keystroke Timing: some preliminary results”, Rand Report R-256-NSF, Rand Corporation, 1980.Google Scholar
- I.Sogukpinar, L. Yalçin, “User identification via keystroke dynamics”, Ist. Üniv. Journal of Electrical and Electronic Engineering, vol. 4, no. 1, 2004, pp. 995-1005.Google Scholar
- E. Yu and S. Cho, “GA-SVM wrapper approach for feature subset selection in keystroke dynamics identity verification”, Proceedings of the International Joint Conference on Neural Networks, vol 3, 2003, pp. 20-2253 – 2257.Google Scholar
- B. Hussien, R. McLaren, and S. Bleha, “An application of fuzzy algorithms in a computer access security system”, Pattern Recognition Letters, vol. 9, no. 1, pp. 39-43.Google Scholar