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Research of Periodic Properties of the Generator Based on m-ary Codes

2022· article· en· W4308082827 on OpenAlex
Roman Korolov, Stanislav Milevskyi, Elnur Baghirov, Musa Mammadov

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

Venue2022 IEEE 3rd KhPI Week on Advanced Technology (KhPIWeek) · 2022
Typearticle
Languageen
FieldComputer Science
TopicChaos-based Image/Signal Encryption
Canadian institutionsCybernet Systems Corporation (Canada)
Fundersnot available
KeywordsRandom number generationCryptosystemCryptographyComputer sciencePseudorandom number generatorDecoding methodsEncoding (memory)Authentication (law)Theoretical computer scienceCode (set theory)Stability (learning theory)AlgorithmComputer security

Abstract

fetched live from OpenAlex

The development of high technologies put forward new requirements for the stability of the cryptographic means used in the post-quantum cryptoperiod (the emergence of a full-scale quantum computer). One of these mechanisms are pseudo-random number generators, which are used in symmetric and asymmetric cryptosystems and authentication mechanisms, while providing both additional and session cryptographic strength. The paper investigates the periodic properties of pseudo-random number generators on m-ary codes, the stability of which is based on the complexity-theoretic problem of syndromic decoding of a random code. An improved method for generating pseudo-random sequences is proposed, which allows generating sequences with a guaranteed period.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.002
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 head0.037
GPT teacher head0.283
Teacher spread0.246 · 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