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
Active behavioural-based authentication systems are challenge-response based implicit authentication systems that authenticate users using the behavioural features of the users when responding to challenges that are sent from the server. They provide a flexible (no extra hardware) and secure second factor for authentication systems, with applications including protection against identity theft and password compromise of web applications. We propose a novel active behavioural authentication system for mobile devices, called DAC (Draw A Circle), where a challenge specifies a set of constraints on a circle and the response is a user drawn circle that satisfies the constraints. We carefully select a set of features that capture behavioural traits of the user which is used to construct a profile for them, then design a matching algorithm that allows users to be authenticated with approximately 95% accuracy. We discuss our implementation, and present our experimental results that show, (i) the accuracy of authentication system and (ii) non-delegateability of profile, guaranteeing that the user cannot pass their credentials to others.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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