Engineering cybersecurity in cyber physical 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
Advances in the interconnected capabilities of cyber physical systems (CPS) affect virtually every engineered system. Today, software approaches dominate all aspects of connecting the physical and cyber worlds in part due to the convergence of computing, control and communications software technologies. Unfortunately, software technologies are more vulnerable to cybersecurity problems than traditional hardware solutions. This workshop aims to develop a research agenda for engineering cybersecurity into cyber physical systems (CPS) through design-time requirements engineering, continuous assurance at runtime, and cognitive security analytics. CPS are distributed, software-intensive smart systems that control tightly integrated computational and physical components. A combination of design-time and runtime techniques are needed to support reasoning about cybersecurity. We advocate a holistic requirements engineering approach, continuous validation with feedback loops supported by models at runtime and networked control, and cognitive security analytics using Watson.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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