Proceedings of the 2007 ACM workshop on Computer security architecture
Bibliographic record
Abstract
It is our great pleasure to welcome you to the First ACM Computer Security Architectures Workshop, held in association with the 14th ACM Computer and Communications Security Conference, November 2nd in Fairfax, Virginia (USA). The call for papers attracted 30 submissions from Asia, Australia, Canada, Europe, South America, and the United States--with authors from 14 different countries. The program committee accepted 9 papers that cover a variety of topics, including side channel attacks, cryptography and authorization systems, authentication, novel authorization systems. We are especially pleased to have a keynote speech by Professor Daniel J. Bernstein on Some Thoughts on Security After 10 Years of qmail 1.0. Qmail is in use at some two million sites, and its architecture is both novel and very efficient; for over 10 years now Professor Bernstein has offered a reward--as yet uncollected--for anyone who can find a security hole in qmail. We also are planning on having a panel on Distributed Authentication, the details of which are not available at press time. We hope that these proceedings will serve as a valuable reference for security researchers and developers. The workshop was created because the design and evaluation of Security Architectures is of fundamental importance to security. And yet, as far as we know, this workshop is unique in its focus on Security Architectures. We hope that this workshop will help to crystallize work in Security Architectures.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 0.017 |
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".