Foreign experience in implementing and developing a cyber risk insurance system: organizational and legal framework
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 concept, role and importance of cyber insurance, current trends in the development of the global cyber insurance market are defined. The grounds and conditions for the development and implementation of a cyber risk insurance system are outlined. The main aspects of the introduction of a cyber insurance system on a global scale are summarized. The experience of the United States, Canada and Australia in creating and developing a cyber insurance system, taking into account existing national characteristics, is studied. The mechanisms for assessing losses of business entities as a result of cyber attacks for the purpose of their compensation, which are used in the analyzed countries, are detailed. Further directions for the introduction and development of the national cyber insurance system are outlined, taking into account the best practices of foreign experience in this area. A list of measures has been determined, the practical implementation of which will facilitate the introduction of cyber insurance in Ukraine.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it