Proceedings of the second ACM workshop on Security and privacy in smartphones and mobile devices
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
It is our great pleasure to welcome you to the Second ACM Workshop on Security and Privacy in Smartphones and Mobile Devices -- SPSM'12, held in association with the 19th ACM Conference on Computer and Communications Security, October 19th, 2012, in Raleigh, NC (USA). The workshop was created last year to organize and foster discussion of security in the emerging area of smartphone and mobile device computing. As organizers of top security venues, we've observed an increasing number of submissions describing novel approaches to solving the challenges of this area. We wanted to provide a dedicated venue to discuss these challenges and promising approaches for future research directions. SPSM'11 was a great success, with an excellent turnout of 80 registered attendees and in-depth discussion. This year, we will continue the 15 minute back-to-back talks followed by 45 minutes of discussion and hope to meet and exceed the high bar that was set. The call for papers attracted 30 submissions from Canada, China, Germany, Greece, India, Iran, Italy, Japan, Lebanon, Nigeria, South Africa, and the United States. The program committee accepted 11 papers that cover a variety of topics, including permission models, user studies, attacks on smartphones, and methods of defense. We are especially pleased to have a keynote speech by Geir Olsen, a Principle Program Manager in the operating systems group on the Windows Phone team, on Windows Phone 8 Security. We hope that these proceedings will serve as a valuable reference for security researchers and developers.
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 | 0.000 | 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 | 0.001 | 0.003 |
| 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