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Record W2127915437 · doi:10.1002/sec.274

An efficient and provably secure public key encryption scheme based on coding theory

2010· article· en· W2127915437 on OpenAlexaff
Rongxing Lu, Xiaodong Lin, Xiaohui Liang, Xuemin Shen

Bibliographic record

VenueSecurity and Communication Networks · 2010
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsOntario Tech UniversityUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceEncryptionScheme (mathematics)Theoretical computer scienceKey (lock)Computer securityCoding (social sciences)Mathematics

Abstract

fetched live from OpenAlex

Abstract Although coding‐based public key encryption schemes such as McEliece and Niederreiter cryptosystems have been well studied, it is not a trivial task to design an efficient coding‐based cryptosystem with semantic security against adaptive chosen ciphertext attacks (IND‐CCA2). To tackle this challenging issue, in this paper, we first propose an efficient IND‐CCA2‐secure public key encryption scheme based on coding theory. We then use the provable security technique to formally prove the security of the proposed scheme is tightly related to the syndrome decoding (SD) problem in the random oracle model. Compared with the previously reported schemes, the proposed scheme is merited with simple construction and fast encryption speed. Copyright © 2010 John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations9
Published2010
Admission routes1
Has abstractyes

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