A Privacy-Preserving Depth-Based Human Identification Framework Using Consumer TrueDepth Sensing

This research presents a privacy-preserving depth-based human identification framework that integrates consumer TrueDepth sensing with hardware-isolated biometric authentication through Apple’s Secure Enclave and LocalAuthentication API. The key contribution is the development of a secure and modular biometric authentication architecture supporting template enrollment, real-time verification, and structured event logging. The framework was experimentally evaluated with 100 participants across normal lighting, low lighting, masking, and facial occlusion conditions. These results demonstrate the feasibility of using consumer depth sensing for secure, repeatable, and privacy-conscious biometric authentication and access control.