Our research got featured in hot topic of Advanced Science "Artificial Intelligence and Machine Learning"
Our recent research on hybrid nanogenerators for keystroke dynamics based biometric authentication and identification using artificial intelligence has been featured in hot topics of Advanced Science journal. In this hot topic, different research articles in AI and ML are featured including material science, medicine, drug discovery, robotics and sociology.
In this work, a keystroke dynamics-based hybrid electromagnetic-triboelectric nanogenerator for biometric authentication and identification system integrated with artificial intelligence is developed with an excellent accuracy of 99%. Cybersecurity is one of the severe issues in this modern computing world where password-based security is being more vulnerable. Keystroke dynamics offer behavioral and contextual information that can distinguish and authorize the individuals based on their typing rhythms. The hybrid electromagnetic-triboelectric nanogenerators/sensors efficiently convert the keystroke mechanical energy into electrical signals, which are fed into an artificial neural network based AI system. The self-powered hybrid sensors-based biometric authentication system integrated with a neural network achieves an accuracy of 99% and offers a promising hybrid security layer against password vulnerability.
