Abstract
The paper is related to creating an algorithm for keystroke dynamics recognition and development of software, which is able to identify users according to their keystroke dynamics. Different characteristics of keystroke dynamics are considered. Probabilistic-statistical methods are compared with neural network algorithms for recognition. The algorithm for recognition was created and implemented. The software was tested with the help of some users. Their keystroke dynamics was analyzed in order to determine an efficiency of the created algorithm.
Highlights
Nowadays, the importance of information is difficult to overstate
Algorithm description Keystroke dynamics is the detailed timing information that describes exactly when each key was pressed and when it was released when concrete person is typing at a keyboard of a computer, gadget etc [6]
The dwell time is shown for the most frequency used letters of the Russian alphabet, because users typed texts in Russian. This picture shows that the dwell time for every letter stays quite similar for different examples of keystroke dynamics
Summary
The importance of information is difficult to overstate. Users should be identified in order to delimit access to it. We should make a point of methods and algorithms of keystroke dynamics recognition. 2. Algorithm description Keystroke dynamics is the detailed timing information that describes exactly when each key was pressed and when it was released when concrete person is typing at a keyboard of a computer, gadget etc [6]. The most common features, which are used to characterize keystroke dynamics, include dwell time, intervals between key presses and overlapping of key presses. Dwell time is a period, during which a key is in the pressed state.
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