  By moving from massive antennas to antenna surfaces for software-defined
wireless systems, the reconfigurable intelligent surfaces (RISs) rely on arrays
of unit cells to control the scattering and reflection profiles of signals,
mitigating the propagation loss and multipath attenuation, and thereby
improving the coverage and spectral efficiency. In this paper, covert
communication is considered in the presence of the RIS. While there is an
ongoing transmission boosted by the RIS, both the intended receiver and an
eavesdropper individually try to detect this transmission using their own deep
neural network (DNN) classifiers. The RIS interaction vector is designed by
balancing two (potentially conflicting) objectives of focusing the transmitted
signal to the receiver and keeping the transmitted signal away from the
eavesdropper. To boost covert communications, adversarial perturbations are
added to signals at the transmitter to fool the eavesdropper's classifier while
keeping the effect on the receiver low. Results from different network
topologies show that adversarial perturbation and RIS interaction vector can be
jointly designed to effectively increase the signal detection accuracy at the
receiver while reducing the detection accuracy at the eavesdropper to enable
covert communications.
