Behavioral Authentication

Behavioral authentication uses an individual's unique behavioral patterns, such as typing rhythm, gait, or gestures, to verify their identity, aiming to replace or supplement traditional methods like passwords. Current research focuses on improving accuracy and efficiency using deep learning models, particularly transformer networks and recurrent neural networks, and exploring techniques to reduce data requirements and enhance privacy. This field is significant for enhancing security in various applications, from mobile devices and smart IoT systems to virtual reality environments, by offering a more user-friendly and robust authentication approach.