Formal model-based argument patterns for security cases
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
Assuring that security requirements have been met and detecting flaws in the early phases of the system development is less expensive than changes after system deployment. The deployment of industrial critical systems requires a security assurance case that represents a credible argument, supported by evidence, demonstrating that the system satisfies its security requirements and objectives. Building arguments and generating evidence to support the claims of an assurance case is of utmost importance and should be done using a rigorous mathematical basis, namely formal methods. This paper proposes an approach to constructing security assurance cases using formal methods. The proposed approach involves the following three steps: (1) decomposing security requirements and deriving security threats; (2) formalizing the system model and security threats; and (3) deriving the security argument patterns supported by the results of the formal verification of the security requirements. We present the derived argument patterns using the Goal Structure Notation pattern notation. We apply the patterns to build security cases of an autonomous drone case study system.
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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