New Guarded-V2X Architecture Secures LLMs in Vehicle Communication

Researchers have developed Guarded-V2X, a novel architecture designed to secure large language models (LLMs) used in vehicle-to-everything (V2X) communication systems. This system addresses prompt-level vulnerabilities that traditional V2X security measures overlook. Guarded-V2X incorporates several layers of defense, including ingress filtering, a safety classifier, policy-constrained generation, and trusted retrieval, to enforce safety boundaries before decisions are executed. Evaluations demonstrated that Guarded-V2X significantly reduces the success rate of intrusions and eliminates unsafe completions in adversarial scenarios without compromising real-time performance. AI

IMPACT Enhances the security and reliability of LLM applications in safety-critical transportation systems.

RANK_REASON The cluster contains a research paper detailing a new architecture for LLM security in V2X systems. [lever_c_demoted from research: ic=1 ai=1.0]

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• alphaXiv
• arXiv
• CatalyzeX
• DagsHub
• Gotit.pub
• Guarded-V2X
• Hugging Face
• large language models
• Rivers State University of Science and Technology
• ScienceCast
• vehicle-to-everything

• paper
• safety
• product

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