  This letter explores the positive side of the adversarial attack for the
security-aware semantic communication system. Specifically, a pair of matching
pluggable modules is installed: one after the semantic transmitter and the
other before the semantic receiver. The module at transmitter uses a trainable
adversarial residual network (ARN) to generate adversarial examples, while the
module at receiver employs another trainable ARN to remove the adversarial
attacks and the channel noise. To mitigate the threat of semantic
eavesdropping, the trainable ARNs are jointly optimized to minimize the
weighted sum of the power of adversarial attack, the mean squared error of
semantic communication, and the confidence of eavesdropper correctly retrieving
private information. Numerical results show that the proposed scheme is capable
of fooling the eavesdropper while maintaining the high-quality semantic
communication.
