INFFLOW-RT IIoT Dataset: Risk-Tagged Smart Grid Transactions for Adaptive Information Flow Control
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| Formato: | Recurso digital |
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2025
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| _version_ | 1866902032520052736 |
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| author | Anagnostopoulou, Argiro Tsinganos, Nikolaos |
| author_facet | Anagnostopoulou, Argiro Tsinganos, Nikolaos |
| contents | <p>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.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16482754 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | INFFLOW-RT IIoT Dataset: Risk-Tagged Smart Grid Transactions for Adaptive Information Flow Control Anagnostopoulou, Argiro Tsinganos, Nikolaos Information flow control Risk-Based Access Control Smart Grid Security Unauthorized Transactions Detection Dynamic Risk Propagation <p>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.</p> |
| title | INFFLOW-RT IIoT Dataset: Risk-Tagged Smart Grid Transactions for Adaptive Information Flow Control |
| topic | Information flow control Risk-Based Access Control Smart Grid Security Unauthorized Transactions Detection Dynamic Risk Propagation |
| url | https://doi.org/10.5281/zenodo.16482754 |