Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions
This addresses security and reliability issues in vehicle-to-everything communications, which is incremental as it builds on existing semantic communication methods.
The paper tackles trust challenges in semantic communication for vehicular networks by proposing a three-layer architecture with mechanisms for eavesdropping defense, attack mitigation, and trust management, validated through a case study.
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.