Real-world graphs such as social networks, communication networks, and rating networks are constantly evolving over time. Many architectures have been de,veloped to learn effective node representations using both graph structure and its dynamics. While the robustness of static graph models is well-studied, the vulnerability of the dynamic graph models to adversarial attacks is underexplored. In this work, we design a novel attack on discrete-time dynamic graph models where we desire to perturb t…