Face recognition as a security system has undergone significant developments, but challenges in live detection are still a major issue in preventing fraud. Liveness detection is a method that helps face recognition security more resistant to fraud. This research aims to address this issue by developing an innovative security system that integrates face recognition with a facial expression game, enhancing live detection and user engagement. The primary objectives are to ensure seamless integration, maintain a fun and challenging user experience, and demonstrate practical applicability. We applied a Waterfall method in our research to ensure a straightforward approach. We successfully applied this system for the door lock-unlock mechanism, simulating a restricted area. YuNet, a face detection model runs in the web interface and controls the NodeMCU to either lock or unlock the door. The study concluded 95% success rate from the participants in making facial expressions: Smile, Normal, and Sad. However, expressing Sadness within the 3-second timeframe posed some difficulties. The average duration for completing the mini-game was approximately 16.31 seconds from the start. The integration of a facial expression game as a liveness detection required careful design to balance security and user engagement that is fun to experience. This research underscores the significance of addressing current challenges in biometric security by integrating an interactive element into the live detection process. The developed system contributes to the field by enhancing the robustness and user experience of face recognition security systems, demonstrating potential for broader application in restricted access scenarios.
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