Research on Communication Technology Security Strategies for Power Systems and Automation in the Information Age
Bibliographic record
Abstract
In today's rapid development of information technology, the scope of power system and its automatic communication technology is expanding day by day, and it is more and more closely related to human's daily life. With the development and improvement of power automation technology, the demand for power equipment is increasing. As one of the important infrastructures of the country, the power system can realize the automatic transmission of data through the use of computer network technology. This not only greatly improves the transmission speed of information, but also relieves the original heavy workload of maintenance personnel, which plays a pivotal role in the development of the power industry. However, due to the fact that the power automation system has encountered many new problems in practical applications, such as network loopholes and network attacks in the process of information transmission, the power grid is prone to errors and control instability in actual operation. How to ensure the security of communication technology in the power industry has become a concern for people in the power industry. Based on the above reasons, from the perspective of electric power automation technology, this paper discusses the information security problems in electric power automation technology, in order to provide useful reference for the information security work in electric power automation technology. The research results show that the security of the communication technology of the automated power system was only about 87% originally, but it can reach about 96% after the reform. This has also directly increased user satisfaction to 97% or more, and at the same time, the operational stability of the power system has also undergone a qualitative leap, an increase of nearly 15% compared to the original.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".