MétaCan
Menu
Back to cohort
Record W2108830258 · doi:10.1109/itcc.2005.6

A countermeasure for EM attack of a wireless PDA

2005· article· en· W2108830258 on OpenAlexaff
Catherine H. Gebotys, C. C. Tiu, X. Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCountermeasureComputer scienceWirelessPower analysisEnergy (signal processing)Computer securityEmbedded systemComputer networkCryptographyTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Future wireless embedded systems will be increasingly powerful, supporting many more applications including one of the most crucial, security. Although many wireless devices offer more resistance to bus probing and power analysis attacks due to their compact size, susceptibility to electromagnetic (EM) attacks must be analyzed. This paper demonstrates, for the first time, a real EM attack on a PDA. A new low energy countermeasure and a new first order differential frequency analysis (DFA) is presented. Real energy measurements are also used to compare the energy overheads of different countermeasures. Results show that the low energy countermeasure thwarts first order differential analysis without large overheads of table regeneration or excessive storage. With the emergence of security applications in PDAs, cellphones, etc., low energy countermeasures for resistance to DFA are crucial for supporting future secure wireless embedded systems.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.313
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

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 designBench or experimental
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

Citations23
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicCryptographic Implementations and SecurityFrench-language works237,207