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Record W2131658256 · doi:10.1145/1084834.1084883

Power-smart system-on-chip architecture for embedded cryptosystems

2005· article· en· W2131658256 on OpenAlexaff
Radu Mureşan, H. Vahedi, Y. Zhanrong, Stefano Gregori

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEmbedded systemComputer sciencePower (physics)MicrocontrollerOverhead (engineering)System on a chipElectric power systemLow-power electronicsComputer hardwareElectronic engineeringEngineeringElectrical engineeringPower consumption

Abstract

fetched live from OpenAlex

In embedded cryptosystems, sensitive information can leak via timing, power, and electromagnetic channels. We introduce a novel power-smart system-on-chip architecture that provides support for masking these channels by controlling, in real-time, the power and the current consumption of a system to predefined programmable values. The main components of the architecture are a processor core, a current sensor module, a dynamically controlled power supply module, a clock frequency control module, and a current injection module. Real-time current measurements and power-aware voltage control are used in closed loop architecture to regulate and minimize the total power consumption of the system. Simulation results show that the current consumption of the system can be regulated to a reference level with reduced power-to-security trade off (power overhead less than 12% of the total power).

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.271
Teacher spread0.256 · 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 designSimulation or modeling
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

Citations19
Published2005
Admission routes1
Has abstractyes

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