Proceedings of the 2009 workshop on New security paradigms workshop
Bibliographic record
Abstract
Since 1992, the New Security Paradigms Workshop (NSPW) has published innovative, diverse, and sometimes controversial work that challenges current paradigms in computer security. This year's papers continue this tradition, with work that touches on many of the major challenges facing computer security today. We had papers on usable authentication, malware detection, filesystem access control, and secure routing. We had papers that challenged the foundations of security practice by questioning how we analyze and evaluate security problems. We even had a paper that argued that users were potentially right to ignore standard security advice. Again this year we had a strong group of submissions from which to build our program. We received 36 submissions; almost three-quarters of these came from academia, with the rest coming from industry (10). We accepted 12 submissions: 11 papers and one panel. The breakdown of the submissions (and acceptances) by geographical region was as follows: 17 submissions had authors from North America (6 accepted), 16 from Europe and the UK (5 accepted), and 3 submissions had authors from other countries (one accepted). To choose our program, first the 13 program committee members reviewed roughly eight submissions each. Once reviews were uploaded to the excellent yet free review system, EasyChair, we had a vigorous online discussion for two weeks. This discussion led to a consensus opinion on almost all of the papers, resulting in the selected papers you see here. As has been a tradition with NSPW from the beginning, all of the papers were discussed extensively at the workshop with all attendees participating. Following upon its success last year, we also divided into small groups to give the authors feedback before they presented their work in front of the entire workshop. In addition, to help improve the quality of the proceedings and provide ongoing support to authors throughout the revision process, all accepted papers were shepherded both before and after the workshop. As should be clear, NSPW thus required a significantly larger time and energy commitment from program committee members, authors, and participants than is the norm for security venues. We believe their effort was worthwhile; after reading this proceedings, we hope you will agree.
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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.105 | 0.045 |
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".