The Model Inversion Eavesdropping Attack in Semantic Communication Systems. (arXiv:2308.04304v1 [cs.IT])

In recent years, semantic communication has been a popular research topic for
its superiority in communication efficiency. As semantic communication relies
on deep learning to extract meaning from raw messages, it is vulnerable to
attacks targeting deep learning models. In this paper, we introduce the model
inversion eavesdropping attack (MIEA) to reveal the risk of privacy leaks in
the semantic communication system. In MIEA, the attacker first eavesdrops the
signal being transmitted by the semantic communication system and then performs …

attack attacks communication deep learning eavesdropping efficiency extract messages popular research systems targeting topic vulnerable