A usability study and critique of two password managers
Bibliographic record
Abstract
We present a usability study of two recent password manager proposals: PwdHash (Ross et al., 2005) and Password Multiplier (Halderman et al., 2005). Both papers considered usability issues in greater than typical detail, the former briefly reporting on a small usability study; both also provided implementations for download. Our study involving 26 users found that both proposals suffer from major usability problems. Some of these are not simply usability issues, but rather lead directly to security exposures. Not surprisingly, we found the most significant problems arose from users having inaccurate or incomplete mental models of the software. Our study revealed many interesting misunderstandings D for example, users reporting a task as easy even when unsuccessful at completing that task; and believing their passwords were being strengthened when in fact they had failed to engage the appropriate protection mechanism. Our findings also suggested that ordinary users would be reluctant to optin to using these managers: users were uncomfortable with relinquishing control of their passwords to a manager, did not feel that they needed the password managers, or that the managers provided greater security.
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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 | 0.043 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".