The article is devoted to increasing the efficiency of technologies of covert monitoring of operators' activity by information and control systems of various purposes for face recognition and emotional state. It is shown that from the standpoint of the possibility of using standard computer peripherals as a sensor for reading biometric parameters, inalienability from the user, the widespread use of information control systems of symbolic password and technological data, the complexity of forgery of biometric information, and the possibility of covert monitoring prospects have the means of keyboard analysis. The necessity of improving the methodology of neural network analysis of keyboard handwriting for authentication and recognition of the emotional state of information computer system operators is substantiated. The prospects of application of convolutional neural networks are determined, which leads to the need to improve the technology of determining the parameters of educational examples in terms of forming the input field of convolutional neural network and forming many parameters of keyboard handwriting to be analyzed. A model of formation of educational examples has been de
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