Identifying WeChat Red Packets and Fund Transfers Via Analyzing Encrypted Network Traffic

WeChat is an extremely popular application in China and among the overseas Chinese users, and two widely used features are giving of 'red packet' (a Chinese customary practice of giving money in red envelope) or fund transfer. Investigation of WeChat red packet and fund transfer transactions is an understudied topic, and hence the focus of this paper. Specifically, we analyze the encrypted network traffic involving WeChat red packet and fund transfer transactions. We segment the traffic into several bursts describing the different actions. Then, we extract relevant red packet transaction and fund transfer features from each burst, which are then used to train a learning-based classifier to distinguish between the different bursts. The findings from our evaluation demonstrate that our proposed approach can accurately identify the actions of red packet transactions and fund transfers, as well as accurately predicting the number of red packet transactions and fund transfers.