MétaCan
Menu
Back to cohort
Record W2514069346 · doi:10.1109/arith.2016.19

A CRC-Based Concurrent Fault Detection Architecture for Galois/Counter Mode (GCM)

2016· article· en· W2514069346 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsWestern University
FundersCMC Microsystems
KeywordsComputer scienceCritical path methodFault coverageCyclic redundancy checkFault detection and isolationRedundancy (engineering)Field-programmable gate arrayOverhead (engineering)Galois theoryEmbedded systemParallel computingAlgorithmMathematicsDecoding methodsEngineering

Abstract

fetched live from OpenAlex

The Galois/Counter Mode (GCM) is a recently adopted mode of operation for symmetric key cryptography to provide both data authenticity and confidentiality. To improve the reliability of hardware implementations of the GCM module, we propose a novel multiple-bit fault detection architecture for hardware implementation of the GCM module using cyclic redundancy check (CRC) codes. By changing the degree of the CRC generating polynomial, one can select the number of parity bits used in the fault detection scheme based on the available resources and required overheads. We derive new formulations for the corresponding fault-detection scheme for the entire GCM loop. Then, we provide FPGA implementation and fault coverage simulation results for different CRC generating polynomials. We show that using six parity bits, one can achieve high fault coverage of close to 100% with the critical path delay overhead of 23% and area overhead of 10.9% while the false alarm is 0.12%.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.286

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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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