On Achieving Cyber Resilience in Digitalized Rail Transit Control Systems
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
Unlike the ICT sector, rail transit has traditionally been viewed as an old-fashioned industry with slower technological advancements. However, the digitalization of rail transit has become essential to achieve significant benefits, such as reducing system complexity and operational costs, while enhancing safety and efficiency. During this ongoing transformation, security remains a top priority, as even a minor breach can lead to severe safety incidents. To thoroughly understand and systematically address this concern, this paper proposes a cyber resilience paradigm tailored to the unique characteristics, security risks, and requirements of rail transit systems. Drawing from an in-depth analysis of relevant contributions in the ICT domain, we redefine and specify the cyber resilience paradigm for rail transit, focusing on theoretical foundations, key techniques, standards, and implementations.
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 | 0.000 |
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