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Record W4280618407 · doi:10.1002/9781119682318.ch12

Privacy Preservation Issues in Cloud Computing

2022· other· en· W4280618407 on OpenAlex
Prasant Kumar Pattnaik, Dac‐Nhuong Le, Souvik Pal

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldComputer Science
TopicCloud Data Security Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsCloud computingObligationInternet privacyCertificationInformation privacyBusinessPrivacy policyPersonally identifiable informationComputer securityPrivacy rightsPrivacy lawControl (management)Computer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Privacy means that a person is free from all interference. Privacy control is the administrative, technical, and physical safeguards employed within agencies to protect and ensure the proper handling of personally identifiable information or prevent activities that create privacy risk. Privacy breaches may create a lot of trouble for cloud users. The American Institute of Certified Public Accountants (AICPA) and Canadian Institute of Charted Accountants (CICA) define privacy as “the right and obligation of individuals and organizations with respect to the collection, use, retention, and disclosure of personal information.”

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.100
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.295
Teacher spread0.266 · 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

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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