Abstract: In order to assist police officers to analyze civil aviation security events, deep LSTM model was used to study subject identification of these events. Firstly, multi-modal information of them was presented by establishing a database, and their time series characteristics were extracted. Then, a deep LSTM model was developed to study and predict subjects of security events. The results show that the proposed model can predict subjects more accurately based on time series characteristics of the events, and even in the presence of noise, it can obtain better prediction results. Moreover, related research results have been successfully applied in SZX international airport.

Key words: civil aviation security event, deep long short-term memory(LSTM) model, event subject, multi-modal, temporal feature