Protocol of change pseudonyms for VANETs
Bibliographic record
Abstract
We propose in this paper a security protocol based on periodic change of pseudonyms. The idea is to avoid illegal traceability of vehicles during their communications and preserve their privacy and confidential information. Two different approaches are proposed. In the first approach, each vehicle asks the central authority a new communication pseudonym after a time t. While in the second approach, each vehicle generates itself after a time t, a new communication pseudonym. Our objective is to permit at least two vehicles to change their pseudonym in the same time interval. We evaluate in this work, the bandwidth used by considering the vehicles speed in each approach. The proposed protocol is based on equidistant distribution of the road side unit and uses the average of speed permitted on the road to evaluate lifetime t of the communication's pseudonyms and certificates. The exchange of information is based on asymmetric and symmetric cryptography scheme and it uses hash function. Our protocol provides authentication, non-repudiation and privacy.
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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 | 0.000 | 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) | 0.001 | 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".