Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions
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Abstract (arXiv)
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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References · 6
- 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
- 2019Local Model Poisoning Attacks to Byzantine-Robust Federated Learningcited by 493
- 2020FLTrust: Byzantine-robust Federated Learning via Trust Bootstrappingcited by 346
- 2024A Survey on Semantic Communication Networks: Architecture, Security, and Privacycited by 22
- 2023The Best Defense is a Good Offense: Adversarial Augmentation against Adversarial Attackscited by 15
- 2022Rethinking Wireless Communication Security in Semantic Internet of Thingscited by 11
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