LLM-Driven Approach for Safe and Secure Network Management by Design in IoT-Based Systems

This paper introduces an LLM-driven design-time workflow for Internet of Things (IoT) and network management system development that combines the generative and summarization capabilities of Large Language Models with the formal rigor of Model-Driven Engineering (MDE). The key novelty lies in grounding LLM-assisted topology design and network management, including reasoning about configuration code to formally verifiable models, enabling security- and safety-aware decisions by design with improved trust and explainability compared with black-box runtime solutions. The approach relies on activity-diagram-based models that provide formal semantics for capturing control flows, decision points, and interactions among IoT devices, edge nodes, and network management components, supporting systematic functional safety validation. Design-time security analysis is realized through MDE combined with Object Constraint Language (OCL) rules, allowing explainable detection of misconfigurations, policy violations, and potential vulnerabilities before deployment. The workflow is evaluated using representative IoT and mobile network management scenarios, demonstrating enhanced effectiveness and up to 15 times reduction in detection and corrective action time for critical tasks.