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

• URL: http://arxiv.org/abs/2606.30595v1
• Date: Mon, 29 Jun 2026 17:36:09 GMT
• Title: Wireless Backdoor Attack and Defense for Semantic Communications over Multiple Access Channel
• Abstract summary: SemCom aims to preserve semantic meaning and task-oriented information over wireless channels.<n>The adoption of SemCom in shared-access wireless networks introduces new vulnerabilities for multi-user semantic inference.<n>This paper considers a SemCom system for two transmitters communicating with a common receiver over a multiple access channel.
• Score: 49.494000480610225
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 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.

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