  We present an approach to classify user validity in survey responses by using
a machine learning techniques. The approach is based on collecting user mouse
activity on web-surveys and fast predicting validity of the survey in general
without analysis of specific answers. Rule based approach, LSTM and HMM models
are considered. The approach might be used in web-survey applications to detect
suspicious users behaviour and request from them proper answering instead of
false data recording.
