MétaCan
Menu
Back to cohort
Record W2246110347 · doi:10.1109/cscloud.2015.30

A Low Storage Phase Search Scheme Based on Bloom Filters for Encrypted Cloud Services

2015· article· en· W2246110347 on OpenAlexaff
Hoi Ting Poon, Ali Miri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEncryptionBloom filterComputer scienceCloud storagePhrase searchCloud computingKey (lock)Scheme (mathematics)Ranking (information retrieval)Search engineInformation retrievalComputer securityComputer networkWeb search queryMathematics

Abstract

fetched live from OpenAlex

Despite the many benefits of cloud technologies, there have also been significant concerns regarding its security and privacy. To address the issues, much efforts have been made towards development of an encrypted cloud system. One of the key features being investigated is the ability to search over encrypted data. Although many have proposed solutions for conjunctive keyword search, few have considered phrase searching techniques over encrypted data. Due to the increased amount of information required to identify phrases, existing phrase search algorithms require significantly more storage than conjunctive keyword search schemes. In this paper, we propose a phrase search scheme, which takes advantage of the space efficiency of Bloom filters, for applications requiring a low storage cost. It makes use of symmetric encryption, which provides computational and storage efficiency over schemes based on public key encryption. The scheme provides simple ranking capability, can be adapted to non-keyword search and is suitable against inclusion-relation attack.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.301
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicCryptography and Data SecurityFrench-language works237,207