Deep Learning-Based Malicious Account Detection in the Momo Social Network

Due to the rapid development of mobile devices and location-based services, location-based social networks (LBSNs) have become very popular in our daily-life. Malicious account detection is very helpful for different kinds of practical applications. In this paper, we explore the malicious account detection problem by introducing a deep learning-based framework. By using the long short-term memory (LSTM) neural network, we are able to build a classifier to achieve the binary classification. By using the real data collected from Momo, a widely used LBSN which has more than 180 million users around the world, we evaluate our framework and the result shows great promise for malicious account detection tasks.