Analysis of the Potential for Using Biometric Characteristics to Identify Insider Threats Based on Psycho-Emotional State

The main biometric characteristics reflecting changes in the psycho-emotional state of a user of an information system are examined. They are ranked using the pairwise comparison method, as a result of which voice and keystroke dynamics are identified as most suitable for further research. Criteria for the preliminary identification of potential internal information security violators based on changes in the considered biometric characteristics are defined. A convolutional neural network model is developed and tested to solve the stated problem.