Keystroke Dynamics Based Hybrid Nanogenerators For Biometric Authentication And Identification Using Artificial Intelligence

This paper reports a new keystroke dynamics-based hybrid nanogenerator for biometric authentication and identification, integrated with artificial intelligence (AI). Keystroke dynamics provide behavioral information that can distinguish individuals based on their typing rhythms. The hybrid nanogenerators convert keystroke energy into electrical signals, which are used by an AI system for authentication.

• A novel keystroke dynamics-based hybrid nanogenerator for biometric authentication.
• Integration with an artificial intelligence (AI) system.
• The system achieves 99% accuracy in user authentication.
• Offers a hybrid security layer to protect against password vulnerabilities.

Hybrid electromagnetic-triboelectric nanogenerators/sensors were used to convert mechanical energy from keystrokes into electrical signals. These signals were then fed into an artificial neural network-based AI system to authenticate and identify users based on their unique typing patterns.

The self-powered hybrid sensors, combined with the neural network, achieved an authentication accuracy of 99%. This demonstrates a promising hybrid security solution that can enhance traditional password-based systems.