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Record W2048600387 · doi:10.1504/ijwmc.2005.008054

The editing generator and its cryptanalysis

2005· article· en· W2048600387 on OpenAlex
Guang Gong, Shaoquan Jiang

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Wireless and Mobile Computing · 2005
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceStream cipherSelf-shrinking generatorGenerator (circuit theory)CryptanalysisShift registerRandomnessRandom number generationCorrelation attackAlgorithmCryptographySequence (biology)Theoretical computer scienceMathematicsElectrical engineeringTelecommunicationsStatistics

Abstract

fetched live from OpenAlex

In this paper, we present a new pseudo-random sequence generator, constructed by using two ternary linear feedback shift registers (LFSR). This new generator is called an editing generator which is a combined model of the clock-control generator (viewed as insertion) and the shrinking generator (viewed as deletion). It is shown that the editing generator has good properties of randomness, such as large periods, high linear spans, large ratio of linear span per symbol and small bias of occurrences of symbols. It is known that clock-control generators and shrinking generators are both insecure. These attacks work only for a single model based stream cipher. Thus, our combined model is secure against these attacks. We devise two different attacks for recovering the initial states of the two LFSRs, i.e., the parity-check attack and the unconstraint embedding attack (analogous to the binary case). Both of these two attacks have exponential running time. It follows that the security is not affected.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.355

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 communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.249
Teacher spread0.242 · 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