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Research PaperResearchia:202606.30015

Wireless Backdoor Attack and Defense for Semantic Communications over Multiple Access Channel

Yalin E. Sagduyu

Abstract

Semantic communication (SemCom) aims to preserve semantic meaning and task-oriented information beyond conventional message recovery over wireless channels. The adoption of SemCom in shared-access wireless networks introduces new vulnerabilities for multi-user semantic inference. This paper considers a SemCom system for two transmitters communicating with a common receiver over a multiple access channel. Each transmitter maps source information into latent semantic representations, while the rec...

Submitted: June 30, 2026Subjects: Cybersecurity; Computer Science

Description / Details

Semantic communication (SemCom) aims to preserve semantic meaning and task-oriented information beyond conventional message recovery over wireless channels. The adoption of SemCom in shared-access wireless networks introduces new vulnerabilities for multi-user semantic inference. This paper considers a SemCom system for two transmitters communicating with a common receiver over a multiple access channel. Each transmitter maps source information into latent semantic representations, while the receiver jointly reconstructs and classifies the semantic information for both transmitters. A selective over-the-air backdoor (Trojan) attack is presented in which an adversary transmits a low-power trigger waveform over the air and injects it into the shared received signal during training. By transmitting the trigger again during testing, this stealthy, low-power attack selectively manipulates the semantic inference for one transmitter while minimally affecting the inference of the other transmitter. To mitigate this vulnerability, a trigger-aware defense mechanism is developed to preserve correct semantic labels under trigger-contaminated wireless observations. The results demonstrate both the vulnerability of shared-access SemCom systems to selective over-the-air backdoor attacks and the effectiveness of trigger-aware robust training for semantic protection.


Source: arXiv:2606.30595v1 - http://arxiv.org/abs/2606.30595v1 PDF: https://arxiv.org/pdf/2606.30595v1 Original Link: http://arxiv.org/abs/2606.30595v1

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Submission Info
Date:
Jun 30, 2026
Topic:
Computer Science
Area:
Cybersecurity
Comments:
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