Formal Trust and Threat Modeling Using Large Language Models

Security modeling, including trust and threat modeling, is a critical process of modern system design and analysis. However, the models are often described in imprecise natural languages, and their inconsistent interpretations and implementations can lead to cybersecurity incidents. In this work, we first introduce an extended Linear Temporal Logic to model the multi-faceted security model of a system to capture its temporal and spatial properties and security guarantees. Then, we manually write 10 security model formulas of real-world systems and attack scenarios. Finally, we fine-Tune a large language model with our manually written models. We evaluate the fine-Tuned model with another set of 9 recent system designs to validate its capability in accurately capturing their security models. Our work provides a formal approach to system security modeling, and it demonstrates the benefits of using large language models in capturing the models of real-world systems.