Biblio
Filters: Author is Sulavko, A. E. [Clear All Filters]
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2017. Users' Identification through Keystroke Dynamics Based on Vibration Parameters and Keyboard Pressure. 2017 Dynamics of Systems, Mechanisms and Machines (Dynamics). :1–7.
The paper considers an issues of protecting data from unauthorized access by users' authentication through keystroke dynamics. It proposes to use keyboard pressure parameters in combination with time characteristics of keystrokes to identify a user. The authors designed a keyboard with special sensors that allow recording complementary parameters. The paper presents an estimation of the information value for these new characteristics and error probabilities of users' identification based on the perceptron algorithms, Bayes' rule and quadratic form networks. The best result is the following: 20 users are identified and the error rate is 0.6%.