Face-Gaze Biometric Fusion for Enhanced Personal Authentication

Objectives: To develop a robust authentication system by combining two authentication modals. The system aims to enhance the security by integrating the gaze-based biometrics in the authentication process, which is difficult to perform spoofing attacks. Methods: The system uses gaze-tracking and face recognition modals to authenticate the user. The user will enter his/her credentials, then the first step of authentication will start where the face recognition modal will authenticate the user by detecting the user’s face, if one is not authenticated in this phase then the user will be omitted. After that the second phase will starts where the system will generate a random 10X10 maze using Depth-First Search algorithm, and then it will extract the x, y coordinates of the maze. The system will capture the user’s real-time eye movement data, and extracts the x, y coordinates of the pupil through a webcam, and compares those coordinates with the maze coordinates if both are matched then the system will provide access to the user else it will omit the user. Findings: Findings show that this approach improves the security of traditional biometric systems, offering a unique form of user authentication. The system tested for accuracy in different environments, and its performance was evaluated based on how well the user’s gaze matches the maze path. Tests across various environments show that the system achieves an accuracy of 92% in matching user gaze to the maze coordinates, also achieved 0% FTE (Failure To Enroll) and 0% FTA (Failure To Acquire). Novelty: The novelty of this project lies in combining biometric eye gaze tracking with real-time maze-based navigation for user authentication. Unlike the traditional biometrics that rely on static features like fingerprints or facial recognition, this system incorporates dynamic tracking of user behavior, specifically gaze patterns, to enhance security. This makes it more resilient to spoofing attacks. Keywords: Biometric Authentication, Deepfake Resistance, Authorization Mechanism, Operational Environments, Human-Centric Security