Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions
Fuente:
arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866915513153617920 |
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| author | Pan, Yanghe Wang, Yuntao Guo, Shaolong Yin, Chengyu Li, Ruidong Su, Zhou Wu, Yuan |
| author_facet | Pan, Yanghe Wang, Yuntao Guo, Shaolong Yin, Chengyu Li, Ruidong Su, Zhou Wu, Yuan |
| contents | Semantic communication (SemCom) has the potential to significantly reduce communication delay in vehicle-to-everything (V2X) communications within vehicular networks (VNs). However, the deployment of vehicular SemCom networks (VN-SemComNets) faces critical trust challenges in information transmission, semantic encoding, and communication entity reliability. This paper proposes an innovative three-layer trustworthy VN-SemComNet architecture. Specifically, we introduce a semantic camouflage transmission mechanism leveraging defensive adversarial noise for active eavesdropping defense, a robust federated encoder-decoder training framework to mitigate encoder-decoder poisoning attacks, and an audit game-based distributed vehicle trust management mechanism to deter untrustworthy vehicles. A case study validates the effectiveness of the proposed solutions. Lastly, essential future research directions are pointed out to advance this emerging field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_20830 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions Pan, Yanghe Wang, Yuntao Guo, Shaolong Yin, Chengyu Li, Ruidong Su, Zhou Wu, Yuan Networking and Internet Architecture Artificial Intelligence Semantic communication (SemCom) has the potential to significantly reduce communication delay in vehicle-to-everything (V2X) communications within vehicular networks (VNs). However, the deployment of vehicular SemCom networks (VN-SemComNets) faces critical trust challenges in information transmission, semantic encoding, and communication entity reliability. This paper proposes an innovative three-layer trustworthy VN-SemComNet architecture. Specifically, we introduce a semantic camouflage transmission mechanism leveraging defensive adversarial noise for active eavesdropping defense, a robust federated encoder-decoder training framework to mitigate encoder-decoder poisoning attacks, and an audit game-based distributed vehicle trust management mechanism to deter untrustworthy vehicles. A case study validates the effectiveness of the proposed solutions. Lastly, essential future research directions are pointed out to advance this emerging field. |
| title | Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions |
| topic | Networking and Internet Architecture Artificial Intelligence |
| url | https://arxiv.org/abs/2509.20830 |