Visual interaction is essential to people’s everyday lives, and identifying someone by their eye movements can successfully prevent unwanted access. The location or spot where a person’s eyes are constantly concentrated is referred to as eye gazing. Artificial intelligence has the ability to produce realistic, human-like faces in today’s technologically strong environment, which increases security risks by gaining access to private data. This model suggest an eye gaze biometric detection system as an innovative way to address this problem. The system will capture the different gaze directions of the user and compared with a maze layout coordinate. To prevent unauthorized access to the intruder’s, authorization will only be provided when the maze path coordinates are matched with the gaze coordinates. This system uses captures the real time user gaze data which are hard to replicate using artificial intelligence which makes the proposed system resistant to spoofing, in contrast to traditional biometric techniques, which are vulnerable to deepfake technology and spoofing attacks. This approach is a solid solution for safe authentication since it offers consistent defense against unwanted access attempts.