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Record W2405997985

Sequential Secret Sharing as a New Hierarchical Access Structure.

2015· preprint· en· W2405997985 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 · 2015
Typepreprint
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSecret sharingComputer scienceAccess structureTheoretical computer scienceContext (archaeology)Verifiable secret sharingCryptographySet (abstract data type)Computer securitySecure multi-party computationCryptographic primitiveHomomorphic secret sharingDistributed computingCryptographic protocolProgramming language
DOInot available

Abstract

fetched live from OpenAlex

Due to the rapid growth of the next generation networking and system technologies, computer net-works require new design and management. In this context, security, and more specifically, access structures have been one of the major concerns. As such, in this article, sequential secret sharing (SQS), as an application of dynamic threshold schemes, is introduced. In this new cryptographic primitive, different (but related) secrets with increasing thresholds are shared among a set of players who have different levels of authority. Subsequently, each subset of the players can only recover the secret in their own level. Finally, the master secret will be revealed if all the secrets in the higher levels are first recovered. We briefly review the existing threshold modification techniques. We then present our construction and compare it with other hierarchical secret sharing schemes such as dis-junctive and conjunctive multilevel secret sharing protocols.

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), Open science, Research integrity
Consensus categoriesOpen science
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 score0.042
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
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0090.030
Research integrity0.0010.004
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 head0.049
GPT teacher head0.332
Teacher spread0.283 · 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