Novel Solution Based on Face Recognition to Address Identity Theft and Cheating in Online Examination Systems


The main objective of this research is to provide a solution for online exam systems by using face recognition to authenticate learners for attending an online exam. More importantly, the system continuously (with short time intervals), checks for learner identity during the whole exam period to ensure that the learner who started the exam is the same one who continued until the end and prevent the possibility of cheating by looking at adjacent PC or reading from an external paper. The system will issue an early warning to the learners if suspicious behavior has been noticed by the system. The proposed system has been presented to eight e-learning instructors and experts in addition to 32 students to gather feedback and to study the impact and the benefit of such system in e-learning environment.

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Fayyoumi, A. and Zarrad, A. (2014) Novel Solution Based on Face Recognition to Address Identity Theft and Cheating in Online Examination Systems. Advances in Internet of Things, 4, 5-12. doi: 10.4236/ait.2014.42002.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Assaf, W., Elia, G., Fayyoumi, A. and Taurino, C. (2007) Prospect of e-Learning: The Case of Jordan. e-Society 2007 —IADIS Multi Conference on Computer Science and Information Systems, Lisbon, 3-8 July 2007.
[2] Ambient Insight (2010) The Worldwide Market for Self-Paced eLearning Products and Services: 2009-2014 Forecast and Analysis Report.
[3] Rosenberg, M.J. (2001) E-Learning: Strategies for Delivering Knowledge in the Digital Age. McGraw-Hill, New York.
[4] Hall, B. and Snider, A. (2000) Glossary: The Hottest Buzz Words in the Industry.
[5] Scalise, K. and Gifford, B. (2006). Computer-Based Assessment in E-Learning: A Framework for Constructing “Intermediate Constraint” Questions and Tasks for Technology Platforms. Journal of Technology, Learning, and Assessment, 4.
[6] Levy, Y. and Ramim, M. (2007) A Theoretical Approach for Biometrics Authentication of e-Exams. Nova Southeastern University, 93-101.
[7] Huszti, A. and Petho, A. (2008) A Secure Electronic Exam System. Informatikafelsöoktatásban, 1-7.
[8] Huang, W., Yen, D. C., Lin, Z.X. and Huang, J.H. (2004) How to Compete in a Global Education Market Effectively: A Conceptual Framework for Designing a Next Generation eEducation System. Journal of Global Information Management, 12, 84-107.
[9] McGinity, M. (2005) Staying Connected: Let Your Fingers Do the Talking. Communications of the ACM, 48, 21-23.
[10] Pillsbury, C. (2004) Reflections on Academic Misconduct: An Investigating Officer’s Experiences and Ethics Supplements. Journal of American Academy of Business, 5, 446-454.
[11] Yang, S. and Verbauwhede, I. (2003). A Secure Fingerprint Matching Technique. Proceedings of the 2003 ACM SIGMM workshop on Biometrics Methods and Applications, California, 89-94.
[12] Hugl, U. (2005) Tech-Developments and Possible Influences on Learning Processes and Functioning in the Future. Journal of American Academy of Business, 6, 250-256.
[13] Flior, E. and Kowalski, K. (2010) Continuous Biometric User Authentication in Online Examinations. Seventh International Conference on Information Technology IEEE Computer Society, Las Vegas, 12-14 April 2010, 488-492.
[14] Yang, M., Kriegman, D. and Ahuja, N. (2002) Detecting Faces in Images: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 34-58.

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