LinkQ demonstrates how knowledge graphs can effectively ground LLMs in factual information for high-stakes security applications.

• Developed and tested an open-source natural language interface that forces LLMs to query knowledge graphs for ground-truth data
• Achieved significant reduction in hallucinations compared to traditional LLM approaches
• Implemented in real-world cybersecurity environments where accuracy is critical
• Provides a practical blueprint for trustworthy AI in sensitive operational contexts

Why it matters: In cybersecurity operations, LLM hallucinations can lead to dangerous misinformation and flawed decision-making. This research offers a validated approach to mitigate these risks while preserving the benefits of natural language interfaces.

Mitigating LLM Hallucinations with Knowledge Graphs: A Case Study