Information and epidemic propagation dynamics in complex networks is truly important to discover and control terrorist attack and disease spread. How to track, recognize and model such dynamics is a big challenge. With the popularity of intellectualization and the rapid development of Internet of Things (IoT), massive mobile data is automatically collected by millions of wireless devices (e.g., smart phone and tablet). In this article, as a typical use case, the impact of network structure on epidemic propagation dynamics is investigated by using the mobile data collected from the smart phones carried by the volunteers of Ebola outbreak areas. On this basis, we propose a model to recognize the dynamic structure of a network. Then, we introduce and discuss the open issues and future work for developing the proposed recognition model.