Communication Protocol Classification Based on LSTM and DBN

In the battlefield, we often don't know the parameters about enemy wireless communication system. Therefore, we need to use electronic reconnaissance equipment to search, intercept, identify and analyze enemy wireless communication signal. However, the exciting electronic reconnaissance methods can only detect signal layer parameters such as signal carrier frequency and bandwidth, and cannot obtain more information. In order to improve the reconnaissance ability, we propose a novel communication protocol classification algorithm based on long short-term memory (LSTM) and deep belief network (DBN). We first introduce the DBN, then simulates communication protocol classification method based on DBN. In order to improve the performance, we optimize the method. We uses the LSTM to pre-process the data to extract the feature firstly. Then we make the feature as the input of DBN to classify the communication protocol. Finally we make simulation to verify the effectiveness of the proposed algorithm. Simulation results show that the proposed algorithm has very good performance to classify the communication protocol.