Global Cyber Security Research Output (1998–2019): A Scientometric Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The main aim of this paper is to analyze the global cyber security literature and to discover underlying trends and developments at the global, national, institutional, and individual level using bibliometric indicators. The publications and citations data for the study were sourced from the SCOPUS database published during 1998–2019. Over this period of 22 years, cyber security research registered a 46.41% growth with an average citation impact of 5.05 citations per paper. Nearly 15% of the total papers were funded by external agencies. The top 10 countries alone accounted for the bulk (76.52%) of output in the subject. The United States leads this list with the highest publication productivity (43.75% of global output). Canada leads the world in terms of relative citation index (1.47). International collaboration has been a major driver of growth in cyber security research. The paper lists most productive organizations, authors, and journals.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.184 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it