A Study of Person Identification using Keystroke Dynamics and Statistical Analysis
Nikhil Ashok Hegde · International Journal of Engineering and Management Research · 2018
In this paper, a basic study of closed-set identification using keystroke dynamics and simple statistical analysis has been carried out. Dwell time, flight time and one additional feature called key affinity are used as useridentifying features. The timing information is passed through a statistical layer to produce mean and standard deviation. This information is combined with key affinity to identify a rank-based person list. In conclusion, we compare the performance of this setup with other setups. This work aims to suggest that a keystroke dynamics system relying on pure statistics as its underlying algorithm may not be sufficiently accurate