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Record W1920843223 · doi:10.1002/sec.586

Chaotic masking for securing RFID systems against relay attacks

2012· article· en· W1920843223 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

VenueSecurity and Communication Networks · 2012
Typearticle
Languageen
FieldComputer Science
TopicChaos-based Image/Signal Encryption
Canadian institutionsToronto Metropolitan UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceRelayComputer securitySimple (philosophy)Scheme (mathematics)Authentication (law)Masking (illustration)Radio-frequency identificationChaoticCryptographyComputer network

Abstract

fetched live from OpenAlex

ABSTRACT The relay attack is a simple yet effective attack against most radio‐frequency identification (RFID) authentication systems. Because of the minimalist design of an RFID system, a lightweight authentication scheme must be designed to provide a strong level of security for low‐cost RFID tags. In this work, we propose a simple but secure masking scheme that counters the relay attack in RFID systems. Our scheme is the first solution based on the chaos suppression theory. We have exploited the chaotic characteristics of a dynamic Lorenz controller to distinguish a legitimate RFID reader from a proxy reader in the relay attack. We also show that the proposed approach is practical using simulation results. Copyright © 2012 John Wiley & Sons, Ltd.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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