  Recently proliferated semantic communications (SC) aim at effectively
transmitting the semantics conveyed by the source and accurately interpreting
the meaning at the destination. While such a paradigm holds the promise of
making wireless communications more intelligent, it also suffers from severe
semantic security issues, such as eavesdropping, privacy leaking, and spoofing,
due to the open nature of wireless channels and the fragility of neural
modules. Previous works focus more on the robustness of SC via offline
adversarial training of the whole system, while online semantic protection, a
more practical setting in the real world, is still largely under-explored. To
this end, we present SemProtector, a unified framework that aims to secure an
online SC system with three hot-pluggable semantic protection modules.
Specifically, these protection modules are able to encrypt semantics to be
transmitted by an encryption method, mitigate privacy risks from wireless
channels by a perturbation mechanism, and calibrate distorted semantics at the
destination by a semantic signature generation method. Our framework enables an
existing online SC system to dynamically assemble the above three pluggable
modules to meet customized semantic protection requirements, facilitating the
practical deployment in real-world SC systems. Experiments on two public
datasets show the effectiveness of our proposed SemProtector, offering some
insights of how we reach the goal of secrecy, privacy and integrity of an SC
system. Finally, we discuss some future directions for the semantic protection.
