The Sunk Costs of Cybersecurity Testing: Who Bears Responsibility?
Bibliographic record
Abstract
This paper intends to bring further clarity regarding the role of the auditor when there is a consideration of a cybersecurity. It seems there is an expectation gap between what the public expects and what the auditor role is, and that cybersecurity testing requires additional skills and efforts. Are auditors currently compensated for the cybersecurity testing? Do they want the scope of the audit to expand to include cybersecurity assessment? Will this lack of clarity impact the corporate governance model that is based on transparency and monitoring? There is limited data available regarding cybersecurity audits and whether such audits lower the threat of cybersecurity. Our analysis suggests that auditors should not have direct responsibility for testing the cybersecurity of a client, rather direct testing should be accomplished by a third party, primarily an auditor specialist. Also, it is time to expect the auditor to become familiar with general cybersecurity skills and standards.
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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 | 0.001 | 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 | 0.001 |
| 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 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".