Recently, drones have been widely used for a variety of purposes, such as surveillance, journalism, environmental protection, disaster management and various leisure activities. However, due to the noneffective monitoring of drones, the accidents of drones interfere with low-flying aircrafts and civil aviations emerge in an endless stream, resulting in many issues in safety. In this paper, we have designed the Dynamic No-fly Zone, which is based on a sphere centered on the current flight with a radius, to accurately model the no-fly zone of drones. Furthermore, in order to deal with the big data produced by the dynamically changed positions of flights and aircrafts, we have presented a Two-Level Dynamic Alert Zone. On top of it, a machine learning algorithm named Positive Logic Model (PLM) is proposed for the realization of the Dynamic No-fly Zone for drones. Without extra hardware support, our heuristic model and algorithm are able to solve the problem of drones interfere with low-flying aircrafts and civil aviations. Simulation experimental results demonstrate the effectiveness of our heuristic approach.