SDRP: a secure distributed revocation protocol for vehicular environments
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
Abstract Secure routing protocols that are based only on cryptographic techniques cannot guarantee security against all attacks. Among solutions that have been proposed to enhance the security in vehicular networks are the distributed revocation protocols, which provide vehicles with the ability to quickly detect and avoid malicious attacks. However, most of the proposed revocation protocols are vulnerable to colluding attacks conducted by malicious nodes, a situation which results in denial of service. In this work, we propose a new and robust distributed revocation protocol for vehicular ad hoc networks, called Secure Distributed Revocation Protocol (SDRP), with the main objective to exclude misbehaving nodes conducting or not a colluding attack from the routing operation in VANET. We present an evaluation analysis of SDRP on the basis of the simulation results and show that our scheme provides a high detection rate of misbehaving nodes with a low rate of false positives even in the presence of a large number of attackers. Copyright © 2012 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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