USABILITY EVALUATION OF MOBILE MULTI-FACTOR AUTHENTICATION BASED ON FACE AUTHENTICATION, GEOLOCATION AND QR CODE

Abstract

The swift progress of information technology has led to the adoption of mobile-based multi-factor authentication (MFA) systems for attendance management, addressing inefficiencies, security issues, and errors inherent in traditional methods. By utilizing multiple layers of authentication—such as face recognition, geolocation, and QR code scanning—these systems significantly enhance security and reliability. This study evaluates the usability of a mobile MFA system, focusing on user-friendliness and learnability. Two iterations of the system were tested using cognitive walkthrough approaches, chosen for their effectiveness in simulating the experience of new users and identifying usability issues in system learnability. The initial version of the system utilized MobileFaceNet_v2, which had an input size of 112x112. This resulted in a false acceptance rate (FAR) of 0.26, a false rejection rate (FRR) of 0.2, and a half total error rate (HTER) of 0.23. Failures in face verifications and inadequate instructions led to significant user dissatisfaction. In the second iteration, improvements were made by providing better instructions during location and QR scan steps, adding a face capture confirmation screen, and increasing the input size of the face anti-spoof detection model to 224x224. This reduced the FAR to 0.11 but increased the FRR to 0.4, resulting in HTER to 0.25. While these updates improved security, usability issues such as ambiguous user feedback and inadequate instructions persisted. These results emphasize the need for an integrated approach that combines both technological improvements in authentication models and enhancements in UI design to create a more user-friendly experience