Hacking in the cloud
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
Cloud computing is a widely expanding and rapidly adopted field of technology. The ability to grant significantly more computational resources than a single machine allows, through use of virtual machines, is incredibly helpful to enterprises that need to meet the demands of hundreds of thousands of concurrent users. However, just as these resources can be used for meaningful purposes, they can also be used for malicious attacks. In this paper, we present the legal and ethical challenges of hacking in the cloud citing specific cyber laws from Canada and the United Arab Emirates, along with the terms of use of cloud service providers. We also present the results of a legal SYN (synchronization) flood attack experiment, utilizing packets with spoofed source internet protocol addresses to determine if this attack works on a cloud service provider. We offer recommendations based on whether or not the cloud platform provides sufficient utility to be used in aiding hackers with their tasks, or if the legal and ethical issues surrounding the implementations ruin any opportunities before development even begins.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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