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JOURNALS // Artificial Intelligence and Decision Making // Archive

Artificial Intelligence and Decision Making, 2019 Issue 2, Pages 15–27 (Mi iipr166)

Data mining

Identification of computer systems users by electroencephalograms parameters in the process of entering the password phrase on the keyboard

A. E. Sulavko, S. S. Zhumazhanova, D. G. Stadnikov

Omsk State Technical University, Omsk, Russia

Abstract: The article discusses the relationship of the keyboard handwriting of a computer user and the parameters of his electroencephalogram (EEG). As part of the work, an experiment was conducted to collect EEG data of 65 subjects who entered the passphrase on different keyboards at different times. An EEG analysis was performed, patterns and EEG parameters (features) were identified that can be used for person biometric identification. A method for identifying a person by the characteristics of the EEG in the process of keyboard input is proposed. A computational experiment was conducted with a large volume of test sample to assess the reliability of recognition of subjects. According to the results of the experiment, 1.62% errors were obtained. At the same time, no dependence of the EEG signs on the keyboard used by the subjects and the time of day, as well as on the variability of the signs with time, was detected.

Keywords: electroencephalogram parameters, pattern recognition, keystroke dynamics, biometric identification, feature space, machine learning, information security.

DOI: 10.14357/20718594190202



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