Aggregated-Proofs Based Privacy-Preserving Authentication for V2G Networks in the Smart Grid
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
Vehicle-to-grid (V2G) as an essential network component of smart grid, provides services by periodically collecting the charging status of a battery vehicle (BV). A BV is normally associated with a default interest group (e.g., power grid operator). When the BV accesses its default charging or communication point, it works in the home mode. The BV may move around and temporarily access other aggregators, and then it works in the visiting mode. In this paper, we first identify that, for an aggregator, BVs have different security challenges when they work in different modes. Then, we propose an aggregated-proofs based privacy-preserving authentication scheme (AP3A) to achieve simultaneous identification and secure identification for different working mode BVs. In AP3A, BVs are differentiated into either home or visiting mode, and multiple BVs can be simultaneously authenticated by an aggregator to conserve communication resources. In addition, the aggregated pseudo-status variation is presented to realize that multiple BVs' power status can be collected as a whole without revealing any individual privacy. We perform comprehensive analysis on the proposed scheme, including attack analysis, security analysis, and performance analysis. It is shown that AP3A can resist major attacks for security protection and privacy preservation, and can be an efficient authentication approach for V2G networks.
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