Cyber-Attack Detection and Isolation for a Fleet of Naval Vessels
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 paper, the problem of attack detection and isolation for a fleet of naval vessels as a multi-agent Cyber-Physical System (CPS) will be addressed. Towards this, in the first step, a time-varying distributed formation control for a fleet of naval vessels as a network of leader-follower multi-agent systems using adaptive observer is presented. After solving formation control for the fleet of naval vessel, the detection and isolation of cyber-attacks for the system based on the obtained protocol will be considered. We demonstrate that the adaptive observers employed by each agent can identify cyber-attacks on communication channels originating from neighboring vessels. Additionally, through the development of a bank of adaptive observers that utilize received information from neighboring vessels and subsequent analysis of available residuals, we can isolate the compromised communication channels. Several cyber-attack scenarios will be discussed to show the performance of the proposed methodology for a fleet of naval vessels.
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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