A preliminary investigation of worm infections in a bluetooth environment
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
Over the past year, there have been several reports of malicious code exploiting vulnerabilities in the Bluetooth protocol. While the research community has started to investigate a diverse set of Bluetooth security issues, little is known about the feasibility and the propagation dynamics of a worm in a Bluetooth environment. This paper is an initial attempt to remedy this situation.We start by showing that the Bluetooth protocol design and implementation is large and complex. We gather traces and we use controlled experiments to investigate whether a large-scale Bluetooth worm outbreak is viable today. Our data shows that starting a Bluetooth worm infection is easy, once a vulnerability is discovered. Finally, we use trace-drive simulations to examine the propagation dynamics of Bluetooth worms. We find that Bluetooth worms can infect a large population of vulnerable devices relatively quickly, in just a few days.
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 | 0.000 | 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