Stealthy Attacks and Robust Detectors for Cyber-Physical Systems With Bounded Disturbances: A Zonotope Approach
Why this work is in the frame
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Bibliographic record
Abstract
This article investigates stealthy attacks on cyber-physical systems that are monitored by a parity-space-based detector and corrupted by bounded disturbances. Specifically, this work proposes a receding horizon attack strategy subject to strict and relaxed stealthiness constraints. Necessary and sufficient conditions for the existence of strictly stealthy attacks of arbitrary lengths are derived. On the defender's side, a robust detector is designed to detect malicious attacks utilizing zonotopes to handle bounded disturbances. A new recursive update method and a reduction operator are proposed to improve the accuracy and reduce the storage space of the detector. Unlike traditional parity-space-based detectors, it is proved that any attack that can completely bypass the robust detector must be bounded. Furthermore, two methods of determining the optimal gains of the proposed detector are provided. The effectiveness of the proposed methods is demonstrated through numerical examples.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it