Securing RDS broadcast messages for smart grid applications
Bibliographic record
Abstract
Efforts to reduce peak electrical demand has led to the introduction of demand response (DR) programs for residences. The RDS network is a strong candidate for delivering DR messages due to its low-cost nature and ubiquitous coverage. However, security concerns arise due to the wireless nature of the communication channel. We present evaluations of cryptographic methods that could be employed to offer source authentication over the RDS network. Simulations are used to determine the impact on the network performance by employing three digital signature protocols (BiBa, HORSE, and ECDSA). The simulation results show that, up to a distance of 90 km, all authentication schemes do not affect message reception by the receivers. ECDSA and HORSE outperform BiBa in terms of message reception beyond 90 km. ECDSA offers higher security than HORSE and BiBa but at the cost of increased computational complexity, in particular at the receivers. In addition, ECDSA has the highest bandwidth overhead.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".