CloudAC: a cloud‐oriented multilayer access control system for logic virtual domain
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
The security issue has been a challenging concern for cloud computing because of the multitenant usage model. In cloud, each application normally runs on a dynamic coalition that is composed by multiple virtual machines (VMs) running on different virtualised service nodes, which the authors called logic virtual domain (LVD). Moreover, the owners of cloud applications, who are also the tenants of cloud, would specify some security policies to control the access to those resources that they have paid for. Therefore the owners of cloud infrastructures have to provide the tenants with the mechanism to correctly configure and enforce the access control policies on resources that are from multiple service nodes, to meet the security requirements from cloud applications. To address the above challenge, this study presents the design and implementation about a multilayer access control architecture for LVD, named CloudAC, aiming to provide isolation control, information flow control and resource‐sharing control among multiple VMs on Xen virtualisation platforms in cloud computing environment. The theory and technology this research formed will provide reliable security guarantee for resource configuration and application deployment on LVDs.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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