  We propose an optimal destination scheduling scheme to improve the physical
layer security (PLS) of a power-line communication (PLC) based
Internet-of-Things system in the presence of an eavesdropper. We consider a
pinhole (PH) architecture for a multi-node PLC network to capture the keyhole
effect in PLC. The transmitter-to-PH link is shared between the destinations
and an eavesdropper which correlates all end-to-end links. The individual
channel gains are assumed to follow independent log-normal statistics.
Furthermore, the additive impulsive noise at each node is modeled by an
independent Bernoulli-Gaussian process. Exact computable expressions for the
average secrecy capacity (ASC) and the probability of intercept (POI)
performance over many different networks are derived. Approximate closed-form
expressions for the asymptotic ASC and POI are also provided. We find that the
asymptotic ASC saturates to a constant level as transmit power increases. We
observe that the PH has an adverse effect on the ASC. Although the shared link
affects the ASC, it has no effect on the POI. We show that by artificially
controlling the impulsive to background noise power ratio and its arrival rate
at the receivers, the secrecy performance can be improved.
