Cognitive-Based Biometrics System for Static User Authentication
Why this work is in the frame
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Bibliographic record
Abstract
In today's globally expanding business world, protecting the identity and transactions of online consumers is crucial for any company to reach out for new markets. This directs digital information technologies towards the adoption of stronger and more secure authentication schemes. Although biometric-based user authentication systems have proven superiority over the traditional ones, there are several barriers for their wide scale deployment and application for INTERNET security; barriers include high expensive equipment, and low precision sensor technologies. In this paper, we propose a novel biometric system for static user authentication. It introduces two new cognitive factors, namely visual scan & detection, and short-term memory. These two factors are homogeneously combined with mouse dynamics in one biometric system. Experimental evaluation was performed using mass enrollment of 275 participants, and Neural Network for classification. Results showed an Equal Error Rate (EER) of 3.88%. The promising achieved performance, in addition to the fact that standard mouse is the only data input device required, make this system ideal for static authentication on the INTERNET.
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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 | 0.001 |
| 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