The Model Inversion Eavesdropping Attack in Semantic Communication
Systems
- URL: http://arxiv.org/abs/2308.04304v1
- Date: Tue, 8 Aug 2023 14:50:05 GMT
- Title: The Model Inversion Eavesdropping Attack in Semantic Communication
Systems
- Authors: Yuhao Chen, Qianqian Yang, Zhiguo Shi and Jiming Chen
- Abstract summary: We introduce the model inversion eavesdropping attack (MIEA) to reveal the risk of privacy leaks in the semantic communication system.
MIEA reconstructs the raw message, where both the white-box and black-box settings are considered.
We propose a defense method based on random permutation and substitution to defend against MIEA.
- Score: 19.385375706864334
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: 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
model inversion attack to reconstruct the raw message, where both the white-box
and black-box settings are considered. Evaluation results show that MIEA can
successfully reconstruct the raw message with good quality under different
channel conditions. We then propose a defense method based on random
permutation and substitution to defend against MIEA in order to achieve secure
semantic communication. Our experimental results demonstrate the effectiveness
of the proposed defense method in preventing MIEA.
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