Bibliographic record
Abstract
While many theoretical approaches to security engineering exist, they are often limited to systems of a certain complexity, and require security expertise that is not widely available. Additionally, in the practice of information system development security is but one of many concerns that needs to be addressed, and security concerns are often dealt with in an ad hoc manner. Security patterns promise to ?ll this gap. Patterns enable an ef?cient transfer of experience and skills. However, representing and selecting security patterns remains largely an empirical task. This becomes the more of a challenge as the number of security patterns documented in the literature grows, and as the patterns proposed by different authors often overlap in scope. Our contribution is to use a more explicit representation of the forces addressed by a pattern in the description of security patterns, which is based on non-functional requirements analysis. This representation helps us decide which patterns to ap-ply in a given design context, and anticipate the effect of using several patterns in combination. Speci?cally this chapter describes an approach for selecting security patterns, and exploring the impact of applying these patterns individually, and in concert with other patterns. Request access from your librarian to read this chapter's full text.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".