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Record W2019409703 · doi:10.1109/tim.2011.2179330

Chaos-Based Security Solution for Fingerprint Data During Communication and Transmission

2012· article· en· W2019409703 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

VenueIEEE Transactions on Instrumentation and Measurement · 2012
Typearticle
Languageen
FieldComputer Science
TopicBiometric Identification and Security
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsEncryptionRobustness (evolution)ChaoticComputer scienceWavelet transformSingular value decompositionAlgorithmChaotic mapFingerprint (computing)Wavelet packet decompositionArtificial intelligenceData miningComputer visionWaveletComputer security

Abstract

fetched live from OpenAlex

In this paper, a security solution during communication and transmission of fingerprint data is proposed in the form of a novel encryption technique based on reversible hidden transform (RHT) and fractional wavelet packet transform (FrWPT). The core idea of the proposed technique is to change the gray values in the spatial domain using RHT followed by the deformation of FrWPT coefficients by singular value decomposition and chaotic map. Hence, security solution relies on both spatial and frequency domains. Finally, a reliable decryption scheme is also presented to reconstruct the original fingerprint image from the encrypted image. Experimental results and security analysis demonstrate the efficiency and robustness of the proposed scheme.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.477

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.102
GPT teacher head0.299
Teacher spread0.197 · 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