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Record W3029665865

Impossible Differential Cryptanalysis of Reduced-Round SKINNY.

2016· preprint· en· W3029665865 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

VenueIACR Cryptology ePrint Archive · 2016
Typepreprint
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsConcordia University
Fundersnot available
KeywordsBlock cipherDifferential cryptanalysisDifferential (mechanical device)Computer scienceLinear cryptanalysisBoomerang attackArithmeticCipherParallel computingAlgorithmMathematicsCryptographyOperating systemPhysicsEncryption
DOInot available

Abstract

fetched live from OpenAlex

SKINNY is a new lightweight tweakable block cipher family proposed by Beierle et al. at CRYPTO 2016. SKINNY has 6 main variants where SKINNY-n-t is a block cipher that operates on n-bit blocks using t-bit tweakey (key and tweak) where \(n=64\) or 128 and \(t=n\), 2n, or 3n. In this paper, we present impossible differential attacks against reduced-round versions of all the 6 members of the SKINNY family in the single-tweakey model. More precisely, using an 11-round impossible differential distinguisher, we present impossible differential attacks against 18-round SKINNY-n-n, 20-round SKINNY-n-2n and 22-round SKINNY-n-3n (\(n=64\) or 128). To the best of our knowledge, these are the best attacks against these 6 variants in the single-tweakey model.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.437
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.005
Research integrity0.0000.001
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 head0.019
GPT teacher head0.294
Teacher spread0.276 · 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