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touch-data

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aliabduljabbar / Password-based-ATO-mitigation-using-timing-and-typing-pattern

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This project explores user authentication on mobile devices through typing patterns, leveraging touch and motion data. Using machine learning models, particularly LSTM, the research demonstrates superior user classification accuracy compared to traditional RNN models, enhancing security against ATO attacks.

lstm rnn mobile-devices machine-learning-models user-authentication motion-data typing-patterns touch-data ato-attacks
  • Updated May 24, 2024
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