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Record W2185939662

Asynchronous Distributed Private-Key Generators for Identity-Based Cryptography

2009· preprint· en· W2185939662 on OpenAlex

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

VenueIACR Cryptology ePrint Archive · 2009
Typepreprint
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRandom oracleComputer scienceAsynchronous communicationScheme (mathematics)EncryptionThe InternetPublic-key cryptographyKey (lock)Computer securityBilinear interpolationCryptographyProtocol (science)Computer networkTheoretical computer scienceDistributed computingMathematicsWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

An identity-based encryption (IBE) scheme can greatly reduce the complexity of sending encrypted messages over the Internet. However, an IBE scheme necessarily requires a private-key generator (PKG), which can create private keys for clients, and so can passively eavesdrop on all encrypted communications. Although a distributed PKG has been suggested as a way to mitigate this problem for Boneh and Franklin’s IBE scheme, the security of this distributed protocol has not been proven and the proposed solution does not work over the asynchronous Internet. Further, a distributed PKG has not been considered for any other IBE scheme. In this paper, we design distributed PKG setup and private key extraction protocols in an asynchronous communication model for three important IBE schemes; namely, Boneh and Franklin’s IBE, Sakai and Kasahara’s IBE, and Boneh and Boyen’s BB1-IBE. We give special attention to the applicability of our protocols to all possible types of bilinear pairings and prove their IND-ID-CCA security in the random oracle model. Finally, we also perform a comparative analysis of these protocols and present recommendations for their use. 1

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0050.003
Research integrity0.0010.002
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 head0.016
GPT teacher head0.273
Teacher spread0.257 · 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