Setpoint Attack Detection in Cyber-Physical Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, we face the problem of detecting setpoint attacks in networked control systems. We consider a setup where the reference signal (also known as setpoint) is generated by a control center remotely located with respect to a standard feedback controller. In this scenario, an attacker with sufficient resources can exploit the communication channel to alter the setpoint signal and ultimately affect the tracking performance of the control system. With respect to this problem, we propose a novel distributed control architecture that, taking advantage of peculiar capabilities of the command governor control paradigm, enables the detection of reference attacks. We formally prove that for constrained linear systems such detector exists. Moreover, by limiting the attacker's disclosure resources with superimposed cryptographically secure pseudorandom signals, we show that the absence of advanced stealthy attacks is also ensured. Finally, a solid numerical simulation investigating setpoint attacks on the flight control system of a single-engine fighter is presented to provide tangible evidence of the features of the presented methodology.
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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) | 0.000 | 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