A behavioral biometrics based authentication method for MOOC's that is robust against imitation attempts

Abstract

Ensuring authorship in online taken exams is a major challenge for e-learning in general and MOOC's in particular. In this paper, we introduce and evaluate a method to verify student identities using stylometry. We present a carefully composed feature set and use it with a K-Nearest Neighbor algorithm. We demonstrate that our method can effectively authenticate authors and is robust against imitation attacks.