ECS‐CP‐ABE: A lightweight elliptic curve signcryption scheme based on ciphertext‐policy attribute‐based encryption to secure downlink multicast communication in edge envisioned advanced metering infrastructure networks
Bibliographic record
Abstract
Abstract As an integral part of the smart grid, advanced metering infrastructure (AMI) implements two‐way communication to enable the smart grid achieving the desired performance improvements over the legacy grid. Integrating communication in addition to the inherited weakness of the power grid paves the way to countless number of security threats to target its communication networks, therefore ensuring secure data exchange is a key concern for AMI networks. In this regard, many schemes are proposed in the literature to secure this two‐way communication, however, very little effort has been focused on multicast transmissions carried out between the control center and a group of smart meters. In order to empower efficient, authentic, and confidential data exchange, this article proposes a new signcryption scheme for multicast downlink communication in edge envisioned AMI networks. The proposed scheme is constructed based on ciphertext‐policy attribute‐based encryption to attain secure fine‐grained access control for the multirecipient communication between the utility control center and a group of smart meters. The novelty of our scheme lies behind the fact that it is an elliptic curve cryptosystem that is pairing free, in opposite to most ABE schemes. Instead of the complex bilinear pairing operations, we exploited faster elliptic curve point multiplication operations to construct the proposed signcryption model. we demonstrate the strength of our protocol in defending against passive, collusion, reply, data modification, and signature forgery attacks. Simulation results prove the efficiency of our protocol in terms of messages size and computation complexity when compared with other schemes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".