{"ID":2865811,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.20830","arxiv_id":"2509.20830","title":"Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2509.20830","url_pdf":"https://arxiv.org/pdf/2509.20830v1","authors":"[\"Yanghe Pan\",\"Yuntao Wang\",\"Shaolong Guo\",\"Chengyu Yin\",\"Ruidong Li\",\"Zhou Su\",\"Yuan Wu\"]","published":"2025-09-25T07:18:20Z","proceeding":"cs.NI","tasks":"[\"cs.NI\",\"cs.AI\"]","methods":"[]","has_code":false}