Poster: TapID: Wearable Sensing Technology for Identity Identification via Tap Vibration Sensing
Jialiang Yan, Jiahua Bao, Z. C. Li, Zhipeng Wang, Jiaxing Du, Jie Liu · 2024
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.