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Record W3149692886

Symmetric-key cryptosystem with DNA technology

2007· article· zh· W3149692886 on OpenAlex
Lü Ming

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

Venue中国科学(F辑:信息科学)(英文版) · 2007
Typearticle
Languagezh
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Biological Computing
Canadian institutionsQueen's University
Fundersnot available
KeywordsDNA computingEncryptionCryptosystemComputer scienceCryptographySymmetric-key algorithmKey (lock)Theoretical computer sciencePublic-key cryptographyComputer securityAlgorithmComputation
DOInot available

Abstract

fetched live from OpenAlex

DNA cryptography is a new field which has emerged with progress in the research of DNA computing. In our study, a symmetric-key cryptosystem was designed by applying a modern DNA biotechnology, microarray, into cryptographic technologies. This is referred to as DNA symmetric-key cryptosystem (DNASC). In DNASC, both encryption and decryption keys are formed by DNA probes, while its ciphertext is embedded in a specially designed DNA chip (microarray). The security of this system is mainly rooted in difficult biology processes and problems, rather than conventional computing technology, thus it is unaffected by changes from the attack of the coming quantum computer. The encryption process is a fabrication of a specially designed DNA chip and the decryption process is the DNA hybridization. In DNASC, billions of DNA probes are hybridized and identified at the same time, thus the decryption process is conducted in a massive, parallel way. The great potential in vast parallelism computation and the extraordinary information density of DNA are displayed in DNASC to some degree.

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), Research integrity
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 score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
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 head0.008
GPT teacher head0.230
Teacher spread0.221 · 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