Requirements for Applying SCIA: A Structured Cyberattack Impact Analysis Approach for ICS
Bibliographic record
Abstract
Modern industrial control systems (ICS) are increasingly integrating cyber-physical components to automate industrial processes. Such integration requires a rigorous exploration of how cyberattack impact propagates through an ICS. However, impact analysis approaches for ICS usually assume the use of specific modeling formalisms and tools, limiting their adoption by analysts familiar with potential alternatives. This work clarifies the rationale behind 20 requirements for applying SCIA: a Structured Cyberattack Impact Analysis approach with different modeling and simulation platforms. Based on a manufacturing ICS case study, we demonstrate two distinct applications of SCIA: (1) Application A, based on formal modeling and verification in UPPAAL-SMC, and (2) Application B, based on simulations in MATLAB/Simulink. We show how both applications are effective at visualizing the evolution of attacks and analyzing temporary and sustained impacts on ICS reliability and availability. In doing so, we detail the methodological differences, the extent of requirement satisfaction, and the associated trade-offs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".