Projection-Based Person Identification

The increasing interest in person identification based on keystroke dynamics can be attributed to several factors. First of all, it is a cheap and widely applicable technique, whereas online services such as internet banking or online tax declaration require reliable person identification methods. Furthermore, there are various attack techniques against the existing identification methods, thus combining the existing methods with new person identification methods could improve the reliability of the identification. Recent research shows that person identification based on machine learning using keystroke dynamics data works surprisingly well. This is because the dynamics of typing is characteristic to users and a user is hardly able to mimic the dynamics of typing of another user. In this paper, we propose to use a projection-based classification technique for the task of person identification based on keystroke dynamics.

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