Verification of Current-State Opacity in Discrete Event Systems by Using Basis Coverability Graphs
Bibliographic record
Abstract
A new approach to the verification of current-state opacity for discrete event systems is proposed in this paper, which is modeled with unbounded Petri nets. The concept of opacity verification is first extended from bounded Petri nets to unbounded Petri nets. In this model, all transitions and partial places are assumed to be unobservable, i.e., only the number of tokens in the observable places can be measured. In this work, a novel basis coverability graph is constructed by using partial markings and quasi-observable transitions. By this graph, this research finds that an unbounded net system is current-state opaque if, for an arbitrary partial marking, there always exists at least one regular marking in the result of current-state estimation with respect to the partial marking not belonging to the given secret. Finally, a sufficient and necessary condition is proposed for the verification of current-state opacity. A manufacturing system example is presented to illustrate that the concept of current-state opacity can be verified for unbounded net systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".