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Record W2375637228

A New Radix-4 Representation Based Multiple Scalar Multiplication Algorithm

2008· article· en· W2375637228 on OpenAlexvenueno aff
Wei Wang

Bibliographic record

VenueMicrocomputer applications · 2008
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Residue Arithmetic
Canadian institutionsnot available
Fundersnot available
KeywordsScalar multiplicationComputer scienceElliptic curve cryptographyElliptic Curve Digital Signature AlgorithmAlgorithmArithmeticScalar (mathematics)SubtractionMultiplication (music)OperandElliptic curve point multiplicationElliptic curveMultiplication algorithmFloating pointHamming weightMathematicsBinary numberPublic-key cryptographyHamming code
DOInot available

Abstract

fetched live from OpenAlex

Many elliptic curve based cryptographic protocols,such as ECDSA signature verification require computation of multiple scalar multiplications such as kP+IQ.Common methods to compute it are the Shamir method and the interleaving method whereas their speed mainly depends on the (joint) Hamming weight of the scalars.The common drawback of these algorithms is that they are based on the radix-2 representations.So no matter what recording is used,only the number of point addition (or subtraction) can be diminished,but the number of point doubling can not be diminished.In this paper,a new recoding method based on the radix-4 representation is proposed.A new radix-4 representation based scalar multiplication algorithm is given. This method adopts point quadruple instead of point doubling,and examines the integer from left to right (from the most significant digit to the least significant digit).This results in the merging of recoding and evaluation stages.So the proposed algorithm can improve the performance and reduce the memory consumption of scalar multiplication operation.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.972
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.236
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

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
Published2008
Admission routes1
Has abstractyes

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