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Record W2063711206 · doi:10.1109/vtcfall.2012.6399217

Robust RFID Authentication for Supply Chain Management

2012· article· en· W2063711206 on OpenAlexaff
Binod Vaidya, Dimitrios Makrakis, Hussein T. Mouftah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRadio-frequency identificationComputer scienceRobustness (evolution)Computer securityAuthentication (law)CryptographySupply chainPublic-key cryptographySupply chain managementGlobal Positioning SystemScheme (mathematics)Key managementEncryptionTelecommunicationsBusiness

Abstract

fetched live from OpenAlex

Radio Frequency Identification (RFID) technology is promising technology in ubiquitous computing area. RFID is used for various applications, ranging from inventory systems to supply chain management solutions such as vehicle fleet management. In supply chain management system, RFID tag is used to identify the object, to which it is attached, without any physical contact in various locations. This makes tags susceptible to information leak. Thus security and privacy issues remain a major issue. Suitability of public key cryptography solutions in RFID system is open research problem. In recent years, practicability of asymmetric cryptography on RFID applications has been discussed. Though EC-GPS scheme allows compact implementation on a tag, it has several flaws. In this paper, we propose robust RFID authentication scheme for supply chain process using improved EC-GPS. We have provided security proof, security analysis and performance evaluation of the proposed scheme to show its robustness.

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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.275

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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2012
Admission routes1
Has abstractyes

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