为车联网语义通信设计可信架构，解决信息传输与节点可靠性难题。
Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions
- 三层架构融合抗窃听、防模型污染与分布式信任管理
- 通过对抗噪声实现主动防御，有效降低信息泄露风险
- 适合关注车联网安全与可信通信的研究者与工程师
语义通信（SemCom）有望显著降低车联网中车与万物（V2X）通信的延迟。然而，车载语义通信网络（VN-SemComNets）在信息传输、语义编码及通信实体可靠性方面面临严峻信任挑战。本文提出一种创新的三层次可信VN-SemComNet架构：引入基于防御性对抗噪声的语义伪装传输机制，用于主动防御窃听；设计鲁棒的联邦编解码训练框架，以缓解编解码器中毒攻击；构建基于审计博弈的分布式车辆信任管理机制，遏制不可信车辆行为。案例研究验证了所提方案的有效性。最后，指出了推动该新兴领域发展的关键未来研究方向。
原文摘要 · Abstract (English)
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.
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