Abstract: Exam malpractice is defined as any intentional wrong doing that is contrary to the examination's standards and intended to provide a candidate an unfair advantage. Exam malpractice, commonly referred to as cheating, is the unethical behavior that students engage in during tests in an effort to improve their grades by taking shortcuts.Exam malpractice is any act or irregular way of testing applicants that violates the laws and customs governing how exams are conducted.In order to pull off the magic they are accustomed to in every exam, many students have neglected their books, which has caused a great deal of harm to the students.Examinee fraud has received a lot of attention in the Nigerian educational system and is considered as a significant problem by not just the test bodies but also school administrators, the entire educational system, the government, and society at large.
Detecting impersonators in examination halls is important to provide a better way of examination handling system which can help in reducing malpractices happening in examination centers. Biometric approach could give a best strategy to decide assessment misbehavior exhaustive the utilization of impersonator. Face Recognition Technology is generally utilized in different applications and competitor can be recognized through facial highlights been removed and carried out by utilizing on calculations or the others. In order to solve this problem, an effective method is required with less manpower. With the advancement of deep learning algorithm, it is easy to solve this problem. In this project developing the framework to recognize the face and also analyze the behavior patterns of students which includes HAAR cascade and Convolutional neural network algorithm.

Keywords: Online exam, Deep learning, Convolutional neural network, Facial features, Behaviors

PDF | DOI: 10.17148/IJARCCE.2022.11807

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