Anti-Spoofing Aided Solutions for Urban Air Mobility: Ground Command Authentication
Bibliographic record
Abstract
The Cyber-Physical System of Urban Air Mobility (UAM) is among the important pivots of the future smart cities that aim at efficient, safe, and sustainable air transportation of people and goods. UAM technology is characterized by integration and the process of private and state-owned in-formation through wireless tele-communication that exchange important messages, including traffic control commands and geo-fencing rules, public safety announcements, and flight path, etc. Therefore, authentication of transmitted messages is among crucial tasks that require integration to the existing navigation systems, in order to protect the airspace against catastrophic consequences of spoofing cyberattacks. This article aims at introducing an intelligent authentication solution for aerial vehicles, to distinguish legitimate Ground Control Centres (GCCs) from adversaries and intruders by means of behavioural analytics, through consistency examination of the transmitted flight plan with prior waypoint trajectories and flight dynamics of the vehicle. In particular, the proposed authentication technology monitors remotely transmitted flight plans to ensure that firstly, there exists a coherent and consistent path with respect to prior waypoints, and secondly, a deliberate dynamic policy that is consistent with optimal energy conservation practices, both of which require access to information that are rarely available to intruders and adversaries. Consequently, flight plans are only obliged if the likelihood of threats or violations to predetermined constraints and traffic rules are acceptable. Numeric simulations of the results have been provided to validate the developed concepts.
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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 | 0.000 |
| 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".