Challenges in evaluating complex IT security management systems
Bibliographic record
Abstract
Performing ecologically valid user studies for IT security management (ITSM) systems is challenging. The users of these systems are security professionals who are difficult to recruit for interviews, let alone controlled user studies. Furthermore, evaluation of ITSM systems inherits the difficulties of studying collaborative and complex systems. During our research, we have encountered many challenges in studying ITSM systems in their real context of use. This has resulted in us investigating how other usability evaluation methods could be viable components for identifying usability problems in ITSM tools. However, such methods need to be evaluated and proven to be effective before their use. This paper provides an overview of the challenges of performing controlled user studies for usability evaluation of ITSM systems and proposes heuristic evaluation as a component of usability evaluations of these tools. We also discuss our methodology for evaluating a new set of usability heuristics for ITSM and the unique challenges of running user studies for evaluating usability evaluation methods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.125 | 0.248 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".