MAAC: Message Authentication Acceleration Protocol for Vehicular Ad Hoc Networks
Bibliographic record
Abstract
Vehicular ad hoc networks (VANETs) adopt the public key infrastructure (PKI) and certificate revocation lists (CRLs) to reliably secure the network. In any PKI system, the authentication of a received message is performed by checking that the certificate of the sender is not included in the current CRL, and verifying the authenticity of the certificate and signature of the sender. In this paper, we propose a message authentication acceleration (MAAC) protocol for VANETs, which replaces the time-consuming CRL checking process by an efficient revocation check process. The revocation check process uses a keyed hash message authentication code (HMAC), where the key used in calculating the HMAC is shared only between non-revoked on-board units (OBUs). In addition, the MAAC protocol uses a novel probabilistic key distribution, which enables non-revoked OBUs to securely share and update a secret key. By conducting security analysis and performance evaluation, the MAAC protocol is demonstrated to be secure and efficient.
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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) | 0.000 | 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".