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Record W2364435379

Improved Data Assured Deletion Model in Cloud Computing Environment

2014· article· en· W2364435379 on OpenAlex
Zhonghu Xu

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer & Network · 2014
Typearticle
Languageen
FieldComputer Science
TopicCloud Data Security Solutions
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsComputer scienceCloud computingEncryptionOverhead (engineering)Computer securityDistributed computingDistributed hash tableHash functionCiphertextHash treeTree (set theory)Computer networkScheme (mathematics)Key (lock)Hash tableOperating system
DOInot available

Abstract

fetched live from OpenAlex

Incloud computing environment, the user hasn't direct management authority for data if the data management performed by cloud service provider. Aiming at this problem, this paper improves the scheme of data assured deletion in cloud environment implemented by using Distributed Hash Tables(DHT) network characteristics, proposes the KDTPC model which allows the data owners to keep the encryption keys generated by key derivation tree and the extracted partial ciphertext at the same time, and eliminates the calculation process of minimum tree keys set when distributing the keys. This scheme can enhance the users' data control in cloud,strengthen the resistance capability of violence attacks, and reduce the time overhead under the premise of ensuring safety performance.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.412
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0030.004
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 head0.028
GPT teacher head0.243
Teacher spread0.214 · 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