A Combined Solution for Conjunctive Keyword Search, Phrase Search and Auditing for Encrypted Cloud Storage
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 has garnered much interest in recent years for its many advantages, but also for its security, privacy concerns. The storage, access of confidential documents has been identified as one of the central problems in the area. Many researchers investigated solutions to search over encrypted documents stored on remote cloud servers. Others proposed schemes for ensuring data integrity or reduce overhead through deduplication while keeping the data encrypted, inaccessible by the cloud operator. While many schemes have been proposed to perform the individual functionalities, less attention has been made to more complete solutions featuring multiple desired functionalities. In this paper, we present a solution that incorporates search, phrase search, auditing where resources are reused for enabling each functionality, achieving an overall smaller storage cost, complexity than implementing each of the functionalities separately. The solution performs search over encrypted documents as efficiently as the leading phrase search scheme in the literature while also enabling unlimited number of audit queries.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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