MétaCan
Menu
Back to cohort
Record W2949376982

Combinatorial Properties of Frameproof and Traceability Codes.

2000· preprint· en· W2949376982 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 · 2000
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsLakehead UniversityUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceTraceabilityDisjoint setsHash functionCombinatorial designCoding (social sciences)Theoretical computer scienceOrder (exchange)Discrete mathematicsMathematicsComputer security
DOInot available

Abstract

fetched live from OpenAlex

In order to protect copyrighted material, codes may be embedded in the content or codes may be associated with the keys used to recover the content. Codes can oer protection by providing some form of traceability for pirated data. Several researchers have studied dierent notions of traceability and related concepts in recent years. \\Strong" versions of traceability allow at least one member of a coalition that constructs a \\pirate decoder" to be traced. Weaker versions of this concept ensure that no coalition can \\frame" a disjoint user or group of users. All these concepts can be formulated as codes having certain combinatorial properties. In this paper, we study the relationships between the various notions, and we discuss equivalent formulations using structures such as perfect hash families. We use methods from combinatorics and coding theory to provide bounds (necessary conditions) and constructions (sucient conditions) for the objects of interest. 1 Introduction In...

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.221
Teacher spread0.193 · 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