Improving user authentication on mobile devices
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
Typing text passwords is challenging when using touchscreens on mobile devices and this is becoming more problematic as mobile usage increases. We designed a new graphical password scheme called Touchscreen Multi-layered Drawing (TMD) specifically for use with touchscreens. We conducted an exploratory user study of three existing graphical passwords on smart phones and tablets with 31 users. From this, we set our design goals for TMD to include addressing input accuracy issues without having to memorize images, while maintaining an appropriately secure password space. Design features include warp cells which allow TMD users to continuously draw their passwords across multiple layers in order to create more complex passwords than normally possible on a small screen. We compared the usability of TMD to Draw A Secret (DAS) on a tablet computer and a smart phone with 90 users. Results show that TMD improves memorability, addresses the input accuracy issues, and is preferred as a replacement for text passwords on mobile devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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