INFFLOW-RT IIoT Dataset: Risk-Tagged Smart Grid Transactions for Adaptive Information Flow Control

This dataset supports the evaluation of the INFFLOW-RT methodology, a real-time, adaptive approach to information flow control in Industrial Internet of Things (IIoT) environments. It includes over 4,000 enriched transactions derived from eight real-world smart grid business processes. Each transaction is modeled as part of a directed graph and annotated with key attributes such as severity, operation type, legality, and dynamically computed risk scores. The dataset enables risk-weighted centrality analysis, multi-order dependency chain exploration, and Bayesian inference-based risk propagation modeling. It is the first publicly described dataset to combine access control, information flow analysis, and dynamic risk estimation in IIoT infrastructures.