  In this paper, intelligent reflecting surfaces (IRSs) are employed to enhance
the physical layer security in a challenging radio environment. In particular,
a multi-antenna access point (AP) has to serve multiple single-antenna
legitimate users, which do not have line-of-sight communication links, in the
presence of multiple multi-antenna potential eavesdroppers whose channel state
information (CSI) is not perfectly known. Artificial noise (AN) is transmitted
from the AP to deliberately impair the eavesdropping channels for security
provisioning. We investigate the joint design of the beamformers and AN
covariance matrix at the AP and the phase shifters at the IRSs for maximization
of the system sum-rate while limiting the maximum information leakage to the
potential eavesdroppers. To this end, we formulate a robust nonconvex
optimization problem taking into account the impact of the imperfect CSI of the
eavesdropping channels. To address the non-convexity of the optimization
problem, an efficient algorithm is developed by capitalizing on alternating
optimization, a penalty-based approach, successive convex approximation, and
semidefinite relaxation. Simulation results show that IRSs can significantly
improve the system secrecy performance compared to conventional architectures
without IRS. Furthermore, our results unveil that, for physical layer security,
uniformly distributing the reflecting elements among multiple IRSs is
preferable over deploying them at a single IRS.
