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A Hybrid Fault Tolerant Approach for AES

2013· article· en· W372232218 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsComputer scienceByteScheme (mathematics)Communication sourceFault toleranceField-programmable gate arrayProcess (computing)ComputationError detection and correctionEmbedded systemFault (geology)Computer hardwareComputer engineeringAlgorithmParallel computingDistributed computingComputer networkOperating system

Abstract

fetched live from OpenAlex

In this paper, a lightweight hybrid fault tolerant approach for AES, which is based on the integration of the algorithm based fault tolerant (ABFT) technique and the fault tolerant technique for s-box byte substitution operation is proposed. Two versions of scheme are presented to satisfy different application requirements. The first general version scheme can detect single error for the whole AES process with high efficiency. Another run-time version scheme is used to immediately terminate the error round with no time delay and no computation wasted on the rest rounds for propagating errors. Utilizing the ready-made arithmetic units in AES, single error can be detected by the sender and prevent the misdirected information from sending out. The results of the hardware FPGA implementation and simulation show that the proposed scheme can be integrated both on software and hardware without making many changes to the original AES implementation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.262
Teacher spread0.240 · 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