Bionic tribo-sensors with sweat and smudge-resistant as electronic skin for personal authentication

Abstract

The increasing prevalence of the internet in our daily lives has made cybersecurity and banking security crucial concerns. Traditional methods such as passwords, fingerprints, and face recognition are becoming replicable and susceptible to hacking. To address this issue, we developed innovative biometric keystroke dynamics for personal authentication utilizing friction electric sensors. A single-electrode triboelectric nanogenerator utilizes the skin as a positive friction layer, allowing direct contact with the sensor. This arrangement enables the detection of subtle mechanical changes during pressing. To mitigate the impact of sweat and organic pollutants, a bionic rose petal friction layer is incorporated, ensuring consistent output and long-term effectiveness. The sensor efficiently converts mechanical keystroke actions into electrical signals for individuals and transmits them to an artificial neural network-based AI system. By utilizing a self-powered sweat- and dirt-proof biometric authentication system, along with the LSTM neural network algorithm, we have achieved an impressive accuracy rate of 97%. This system provides a promising security layer against password cracking and user privacy vulnerabilities.