Fog Computing usefully extends Cloud to the edge of the network for the sake of meeting users’ expanding demand for low latency. However, due to its scattered distribution and open architecture, fog nodes are highly vulnerable to security threats, resulting in an inevitable sharp conflict between quick response time and high data security. This conflict motivates the need for effective data placement among fog nodes towards a trade-off between security and time. Existing studies merely offer independent solutions by considering either security or response time. By contrast, we establish a dynamic multi-objective optimization model in this article by optimizing security and response time simultaneously. With this model, we propose an efficient evolutionary algorithm, referred to asDynamic Interactive Security-and-Time cognizant algorithm(DIST), to obtain optimal data placement strategies under Fog environments. To improve efficiency,DISTallows users to gradually incorporate their preference information into the search process so as to find their most preferred solutions without exploring the whole search space. We demonstrate the superiority ofDISTby rigorous comparison with the most state-of-art data placement strategy and other well-applied strategies. Experimental results manifest thatDISToutperforms other strategies in obtaining solutions with higher data security and shorter response time. Furthermore,DISTis capable of efficiently and continuously tracking the Pareto optimal solution under dynamically changing Fog environments while other existing strategies cannot.