Abstract
Semantic communication allows the receiver to know the intention instead of
the bit information itself, which is an emerging technique to support real-time
human-machine and machine-to-machine interactions for future wireless
communications. In semantic communications, both transmitter and receiver share
some common knowledge, which can be used to extract small-size information at
the transmitter and recover the original information at the receiver. Due to
different design purposes, security issues in semantic communications have two
unique features compared to standard bit-wise communications. First, an
attacker in semantic communications considers not only the amount of stolen
data but also the meanings of stolen data. Second, an attacker in semantic
communication systems can attack not only semantic information transmission as
done in standard communication systems but also attacks machine learning (ML)
models used for semantic information extraction since most of semantic
information is generated using ML based methods. Due to these unique features,
in this paper, we present an overview on the fundamentals and key challenges in
the design of secure semantic communication. We first provide various methods
to define and extract semantic information. Then, we focus on secure semantic
communication techniques in two areas: information security and semantic ML
model security. For each area, we identify the main problems and challenges.
Then, we will provide a comprehensive treatment of these problems. In a
nutshell,this article provides a holistic set of guidelines on how to design
secure semantic communication systems over real-world wireless communication
networks.