MétaCan
Menu
Back to cohort
Record W2949933527

Unified Point Addition Formulæ and Side-Channel Attacks.

2005· preprint· en· W2949933527 on OpenAlexaff
Douglas Stebila, Nicolas Thériault

Bibliographic record

VenueIACR Cryptology ePrint Archive · 2005
Typepreprint
Languageen
FieldComputer Science
TopicCryptography and Residue Arithmetic
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSide channel attackComputer scienceAffine transformationElliptic curvePoint (geometry)CryptographyElliptic curve point multiplicationElliptic curve cryptographyChannel (broadcasting)Tripling-oriented Doche–Icart–Kohel curveArithmeticKey (lock)AlgorithmMathematicsComputer securityPure mathematicsEncryptionPublic-key cryptographyGeometryTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Abstract. The successful application to elliptic curve cryptography of side-channel attacks, in which information about the secret key can be recovered from the observation of side channels like power consumption, timing, or electromagnetic emissions, has motivated the recent development of unified formulæ for elliptic curve point operations. In this paper, we show how an attack introduced by Walter can be improved and used against the unified formulæ of Brier, Déchène and Joye when it relies on a standard field arithmetic implementation, both in affine and projective coordinates. We also describe how the field arithmetic might be implemented to obtain more uniform operations that avoid this type of attack.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueIACR Cryptology ePrint ArchiveSame topicCryptography and Residue ArithmeticFrench-language works237,207