Research on Anonymous Authentication of Vehicle to Grid Users Based on Group Signature
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
In order to solve the problem that the privacy information of the vehicle to grid user is leaked, which endangers the safety of users' lives and properties. In this paper, a V2G user anonymous authentication scheme based on group signature is proposed to realize the user anonymous authentication of vehicle to grid. In order to realize the anonymous authentication of the charging station to the EV, the scheme mainly adopts group signature algorithm to achieve anonymous authentication between the EV and the power grid. In the process of authentication, only the trusted center has the real identity of the user to ensure the anonymous interaction between electric vehicle and power grid. The aggregation unit records the EV information by combining a complete subtree method and Chinese remainder theorem, so that other members do not need to change the key in the process of EV revocation. According to the security analysis, this scheme can ensure the confidentiality, integrity, effectiveness and non-repudiation of information in V2G network. The performance analysis shows that this scheme can reduce the computing and communication costs of the vehicle to grid.
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 | 0.000 | 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 it