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Record W2170623172 · doi:10.1109/date.2005.32

A Public-Key Watermarking Technique for IP Designs

2005· article· en· W2170623172 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

VenueDesign, Automation, and Test in Europe · 2005
Typearticle
Languageen
FieldComputer Science
TopicDigital Rights Management and Security
Canadian institutionsUniversité de MontréalConcordia University
Fundersnot available
KeywordsDigital watermarkingRobustness (evolution)Computer scienceWatermarkEmbeddingDigital Watermarking AllianceComputer securityKey (lock)Finite-state machinePublic-key cryptographyTheoretical computer scienceAlgorithmEncryptionArtificial intelligence

Abstract

fetched live from OpenAlex

Sharing IP blocks in today's competitive market poses significant high security risks. Creators and owners of IP designs want assurances that their content will not be illegally redistributed by consumers, and consumers want assurances that the content they buy is legitimate. Recently, digital watermarking emerged as a candidate solution for copyright protection of IP blocks. In this paper, we propose a new approach for watermarking IP designs based on the embedding of the ownership proof as part of the IP design's finite state machine (FSM). The approach utilizes coinciding as well as unused transitions in the state transition graph of the design. Our approach increases the robustness of the watermark and allows a secure implementation, hence enabling the development of the first public-key IP watermarking scheme at the FSM level. We also define for our approach, and use experimental measures to prove its robustness.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.060
GPT teacher head0.246
Teacher spread0.186 · 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