An assessment of the role of the common criteria in the international mutual recognition of trusted information system evaluations
Bibliographic record
Abstract
This research study documents the twelve year evolution of diverse international criteria for evaluating trusted information systems. The study explains what trusted information systems are, why they are needed, and how their security functionality and assurance is expressed and measured. The research traces the development of the U.S., European, Canadian, and Japanese criteria for evaluating trusted information systems, and addresses the effort to replace the existing U.S. criteria. The study examines the need for mutual recognition of trusted information system evaluations by looking at the evaluation processes and the rating schemes in the U.S., Europe, and Canada. It further discusses the consequences of diverse international criteria and shows how the lack of mutual recognition of evaluations is causing significant problems for those that criteria were initially developed to help, such as computer vendors, allied nations and user organizations, systems integrators, and evaluators. The study looks at the attempts by the North Atlantic Treaty Organization (NATO) and the International Standards Organization (ISO) to harmonize the national and multinational criteria. It also reviews the current international harmonization effort by the Common Criteria Editorial Board (CCEB). The research study demonstrates the thesis that there are three integral parts of the formula to achieve the goal of international mutual recognition of trusted information system evaluations, and that all three parts need to be achieved in parallel. To that end, this research shows that the joint effort by the governments of the United States and Canada, together with the Commission of the European Communities, to produce a harmonized set of common international criteria for developing and evaluating trusted information systems is necessary, but insufficient because additional international standards for a common evaluation process and for a set of common evaluator qualifications are also needed. (Abstract shortened by UMI.).
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".