Secure and Lightweight Authentication Scheme for Smart Metering Infrastructure in Smart Grid
Bibliographic record
Abstract
In this article, a secure and lightweight authentication scheme, which provides trust, anonymity, and mutual authentication, with reduced energy, communicational, and computational overheads, is proposed for resource-constrained smart meters (SMs). The designed mutual authentication-based key agreement protocol leverages the advantages of fully hashed menezes-qu-vanstone key exchange mechanism along with Elliptic curve cryptography and one-way hash functions. Moreover, it allows to securely establish and verify the trust between the two communicating parties, i.e., SMs and neighbourhood area network gateway. These entities communicate over the insecure channel and form an important component of the smart metering infrastructure. Furthermore, extensive performance evaluation validates the supremacy of the designed protocol over the state-of-the-art in furnishing higher security features with minimal communicational and computational overheads. The obtained results also reflect that the proposed protocol is fit for implementation on resource-constrained SMs as it leads to minimal energy consumption.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".