A Blockchain-Based Cybersecurity Model for Unauthorized Outage Prevention in Ami/Scada Distribution Systems in MéXico
Bibliographic record
Abstract
In the context of critical infrastructure, electrical distribution systems face increasing threats from cyberattacks that could lead to unauthorized power outages, both in high- and low-voltage networks. This work proposes a cybersecurity software model that utilises an authorization scheme based on digital tokens and blockchain technology to control and validate commands that affect service continuity in operational outage processes. The model is designed to integrate with Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) systems, enabling distributed verification, command traceability, and resilience to unauthorized access. Through smart contracts and immutable records, it is guaranteed that only entities with valid credentials and decentralized authorization can execute critical actions such as outages or reconnections. This paper presents a new proposed approach that could improve the operational resilience of the system, reduce the potential for attacks, and enable secure and auditable management of the electrical grid.
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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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".