Taxonomy and Accurate Survey of Fake Face Recognition System in E-learning Platforms

E-learning platforms changed the way people learn, they are accessible and flexible; Unfortunately, the trend of online education has also brought an increase in fraud activity too and among them is identity verification. Moreover, the threat of fake face recognition, which allows users to get pass from authenticity procedure by presenting an altered/synthetic facial image, is immense and gives birth this vulnerability into E-learning environments. In this paper, we aggregate the knowledge regarding such capture attacks developed in past years and revisit them together with recent related works. This paper also presents the real-time threat scenario for such attacks on academic integrity which has been incorporated while framing a multi-layer approach to secure faculty students from these kind of deceptions in facial recognition system E-learning platforms. This paper will be useful for researchers who aim to research in the areas of fake face detection in e-learning platforms or in other fields and platforms.