Identity Verification and Fraud Detection During Online Exams With aPrivacy Compliant Biometric System

International audienceDistant learning is an alternative solution to education when the learner is far from the school or cannot attendcourses for professional or medical reasons. The main objective of this work is to design a smart applicationof remote exams, using a multibiometric system combining face with deep learning and keystroke dynamicsto verify the identity of the learner. Privacy protection is consider in this work as an important issue becausemany personal data are processed in the proposed solution. We consider in this paper experiments under real-life conditions to identify abnormal behaviours with confidence indicators. We show the system ability tomake the correct decision while preserving learner’s privacy