Poster: TapID: Wearable Sensing Technology for Identity Identification via Tap Vibration Sensing

The increasing integration of wearable devices in daily activities has elevated the need for robust authentication methods that safeguard user data. Traditional knowledge-based and biometric authentication techniques face challenges in wearable contexts, including privacy risks and hardware limitations. We propose TapID, a novel authentication approach that leverages the unique relaxation vibrations of wrist bone conduction following a tapping gesture. This method bypasses the need for intrusive data collection and expensive hardware. Our method employs an energy window extraction algorithm and cross-correlation to isolate biometric signals, followed by feature extraction and k-NN classification. Tested on a Raspberry Pi, TapID authenticated users with a 93% success rate in a preliminary trial involving ten individuals, demonstrating its potential for secure and user-friendly wearable authentication.