  In this correspondence, we study the physical layer security in a stochastic
unmanned aerial vehicles (UAVs) network from a network-wide perspective, where
the locations of UAVs are modeled as a Mat$\acute{\text{e}}$rn hard-core point
process (MHCPP) to characterize the minimum safety distance between UAVs, and
the locations of users and eavesdroppers are modeled as a Poisson cluster
process and a Poisson point process, respectively. UAVs adopt zero-forcing
precoding to serve multiple ground users and emit artificial noise to combat
eavesdropping. We derive the approximations for the coverage probability and
secrecy probability of a typical user, with which we derive the secrecy
throughput of the whole network. Numerical results show the analytical results
can well approximate the simulation results. Impacts of parameters on the
secrecy performance are shown.
