Based on the analysis of behavioral characteristics, the main indicators that provide the greatest accuracy in identifying users of mobile devices are identified. As part of the research, software has been written to collect touchscreen data when performing typical user actions. Identification algorithms are implemented based on machine learning algorithms and accuracy is shown. The results obtained in the study can be used to build continuous identification systems.

Keywords: user behavior, touch screen, continuous identification, biometrics, dataset, classification, deep learning, recurrent neural network, mobile device