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Unmanned aerial vehicles (UAVs) can be employed as aerial base stations to support communication for the ground users (GUs). However, the aerial-to-ground (A2G) channel link is dominated by line-of-sight (LoS) due to the high flying altitude, which is easily wiretapped by the ground eavesdroppers (GEs). In this case, a single UAV has limited maneuvering capacity to obtain the desired secure rate in the presence of multiple eavesdroppers. In this paper, we propose a cooperative jamming approach by letting UAV jammers help the UAV transmitter defend against GEs. To be specific, the UAV transmitter sends the confidential information to GUs, and the UAV jammers send the artificial noise signals to the GEs by 3D beamforming. We propose a multi-agent deep reinforcement learning (MADRL) approach, i.e., multi-agent deep deterministic policy gradient (MADDPG) to maximize the secure capacity by jointly …