Awareness and Assistance: General Drivers' Cyber Threat Identification and the Role of an In-Vehicle Console Display
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
This online survey-based study investigated human drivers' awareness of cyber threats to automated vehicles from a human-centric perspective. Findings show drivers more readily identify explicit threats, particularly affecting vehicle motion, but struggle to grasp their origins. The study also assesses the effectiveness of Tesla Model 3's console display, as an example of a popular modern vehicle dashboard interface, in aiding threat identification, with drivers viewing it as moderately helpful. However, the driver's performance in identifying threat details is limited. This work's results highlight the challenges drivers face in responding to cyber threats and their need for information displayed for cyber threat diagnostics, actionable guidance, and a potential dedicated operation center for timely, systematic cyber threat management in modern driving systems.
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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