Retrieval Augmented Generation-based Large Language Models for Bridging Transportation Cybersecurity Legal Knowledge Gaps

• URL: http://arxiv.org/abs/2505.18426v1
• Date: Fri, 23 May 2025 23:40:10 GMT
• Title: Retrieval Augmented Generation-based Large Language Models for Bridging Transportation Cybersecurity Legal Knowledge Gaps
• Authors: Khandakar Ashrafi Akbar, Md Nahiyan Uddin, Latifur Khan, Trayce Hockstad, Mizanur Rahman, Mashrur Chowdhury, Bhavani Thuraisingham,
• Abstract summary: This study introduces a Retrieval-Augmented Generation (RAG) based Large Language Model (LLM) framework designed to support policymakers.<n>The framework focuses on reducing hallucinations in LLMs by using a curated set of domain-specific questions to guide response generation.<n>Our analysis shows that the proposed RAG-based LLM outperforms leading commercial LLMs across four evaluation metrics.
• Score: 14.261871331519567
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As connected and automated transportation systems evolve, there is a growing need for federal and state authorities to revise existing laws and develop new statutes to address emerging cybersecurity and data privacy challenges. This study introduces a Retrieval-Augmented Generation (RAG) based Large Language Model (LLM) framework designed to support policymakers by extracting relevant legal content and generating accurate, inquiry-specific responses. The framework focuses on reducing hallucinations in LLMs by using a curated set of domain-specific questions to guide response generation. By incorporating retrieval mechanisms, the system enhances the factual grounding and specificity of its outputs. Our analysis shows that the proposed RAG-based LLM outperforms leading commercial LLMs across four evaluation metrics: AlignScore, ParaScore, BERTScore, and ROUGE, demonstrating its effectiveness in producing reliable and context-aware legal insights. This approach offers a scalable, AI-driven method for legislative analysis, supporting efforts to update legal frameworks in line with advancements in transportation technologies.

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