Proceedings of the 2004 ACM workshop on Formal methods in security engineering
Bibliographic record
Abstract
This volume contains the proceedings of the Second ACM Workshop on Formal Methods in Engineering (FMSE 2004) held in Washington D.C., October 29th, in conjunction with the 11th ACM Conference on Computer and Communications Security. The purpose of FMSE is to bring together researchers and practitioners from both the security and the software engineering communities, from academia and industry, who are working on applying formal methods to designing and validating large-scale security-critical systems. The scope of the workshop covers security and formal-methods related aspects of: security specification techniques, formal trust models, combination of formal techniques with semi-formal techniques like UML, formal analyses of specific security properties relevant to software development, security-preserving composition and refinement of processes, faithful abstractions of cryptographic primitives and protocols in process abstractions, integration of formal security specifications, as well as refinement and validation techniques in development methods and tools. The paper selection process was very competitive this year. The call for papers attracted 25 submissions from Asia, Canada, Europe, Africa, and the United States. The program committee accepted 9 papers for presentation at the workshop, which means that many high-quality papers had to be rejected. In addition, the program included an invited talk on Security Analysis of Network Protocols by John C. Mitchell as well as an invited talk on Model-driven development of Components by Prem Devanbu.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.039 | 0.013 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".