SAT : Security in the air using Tesla
Bibliographic record
Abstract
Automated Dependent Surveillance - Broadcast (ADS-B) is an aircraft surveillance technology introduced as part of the US Next-Generation Air Transportation System (NextGen) initiative, in which aircraft broadcast their position based on satellite navigation (e.g. GPS). This information can then be used by other aircraft for traffic awareness and collision avoidance (TCAS), and by ground personnel to provide air traffic control (ATC) services. Unfortunately, ADS-B presents important security problems, since there are no integral mechanisms for message authentication nor message integrity verification. In this paper, we propose SAT, a secure, backward-compatible replacement for ADS-B. SAT uses the TESLA broadcast authentication protocol, a hybrid solution that combines the advantages of symmetric cryptography (low use of bandwidth) with those of asymmetric cryptography (no shared keys). Our proposal adapts the TESLA constructs in order to make it suitable for use in ATC and collision avoidance. In particular, we replace the synchronization mechanism of TESLA with the use of satellite time, thus making the implementation more lightweight. We also use a public key infrastructure based on the air traffic control hierarchy (including national civil aviation authorities and potentially ICAO), in order to allow for SAT to be used not only for aircraft authentication but also for aircraft flight authorization. We implemented the SAT protocol on SDR and performed laboratory experiments in order to measure computation and transmission overheads, and to determine the shortest authentication delay we could achieve. In particular, we explored the trade-off between interval duration and bandwidth use. Finally, we tested our new protocol on SDR.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".