  Online information systems currently heavily rely on the username and
password traditional method for protecting information and controlling access.
With the advancement in biometric technology and popularity of fields like AI
and Machine Learning, biometric security is becoming increasingly popular
because of the usability advantage. This paper reports how machine learning
based face recognition can be integrated into a web-based system as a method of
authentication to reap the benefits of improved usability. This paper includes
a comparison of combinations of detection and classification algorithms with
FaceNet for face recognition. The results show that a combination of MTCNN for
detection, Facenet for generating embeddings, and LinearSVC for classification
outperforms other combinations with a 95% accuracy. The resulting classifier is
integrated into the web-based system and used for authenticating users.
