A Comparative Long-Term Study of Fallback Authentication Schemes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fallback authentication, the process of re-establishing access to an account when the primary authenticator is unavailable, holds critical significance. Approaches range from secondary channels like email and SMS to personal knowledge questions (PKQs) and social authentication. A key difference to primary authentication is that the duration between enrollment and authentication can be much longer, typically months or years. However, few systems have been studied over extended timeframes, making it difficult to know how well these systems truly help users recover their accounts. We also lack meaningful comparisons of schemes as most prior work examined two mechanisms at most. We report the results of a long-term user study of the usability of fallback authentication over 18 months to provide a fair comparison of the four most commonly used fallback authentication methods. We show that users prefer email and SMS-based methods, while mechanisms based on PKQs and trustees lag regarding successful resets and convenience.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it