Secure Semantic Communication for Image Transmission in the Presence of Eavesdroppers
arxiv(2024)
摘要
Semantic communication (SemCom) has emerged as a key technology for the
forthcoming sixth-generation (6G) network, attributed to its enhanced
communication efficiency and robustness against channel noise. However, the
open nature of wireless channels renders them vulnerable to eavesdropping,
posing a serious threat to privacy. To address this issue, we propose a novel
secure semantic communication (SemCom) approach for image transmission, which
integrates steganography technology to conceal private information within
non-private images (host images). Specifically, we propose an invertible neural
network (INN)-based signal steganography approach, which embeds channel input
signals of a private image into those of a host image before transmission. This
ensures that the original private image can be reconstructed from the received
signals at the legitimate receiver, while the eavesdropper can only decode the
information of the host image. Simulation results demonstrate that the proposed
approach maintains comparable reconstruction quality of both host and private
images at the legitimate receiver, compared to scenarios without any secure
mechanisms. Experiments also show that the eavesdropper is only able to
reconstruct host images, showcasing the enhanced security provided by our
approach.
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