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An ergonomic Windows utility that maps arrow and navigation keys directly to the home row. Boost typing speed and stay in the flow by using Alt combinations to navigate, delete, and jump lines without ever lifting your hands.
Records the keystroke timing data and creates a model. Applies learning algorithms and statistical models to differentiate between a valid user and an intruder
Our project considers various machine learning and deep learning techniques like CNN and RNN based on free-text keystroke features for user authentication. Moreover, we will develop a simple UI to test new users.
Human interaction verification through behavioral biometrics. Analyzes mouse movement, click patterns, keystroke dynamics, scroll behavior, touch pressure, and device sensors to distinguish humans from bots.