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Record W2108864584 · doi:10.1109/icis.2012.49

Feasibility Evaluation of a Secured Architecture for 2-Party Mobile Payments (SA2pMP)

2012· article· en· W2108864584 on OpenAlexaff
Y. Zhu, Jacqueline E. Rice, Brian Dobing, Ge Bao Shan, Mianxiong Dong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsComputer scienceComputer securityMobile paymentArchitectureNon-repudiationJavaConfidentialityAuthentication (law)Mobile devicePaymentAnonymityMobile computingCryptographyProcess (computing)Embedded systemComputer networkOperating systemWorld Wide Web

Abstract

fetched live from OpenAlex

Mobile technology has already had a major impact on the financial industry. With the growing acceptance of mobile transactions, security issues require more attention. The proposed secured architecture for 2-party mobile payments (SA2pMP) was designed to satisfy the four properties of confidentiality, authentication, integrity and non-repudiation that are demanded by any secure system. As an extension following [1] and [2], a PC-based simulation is conducted to evaluate the feasibility of the proposed architecture. This paper introduces the computer based simulation and the feasibility evaluation process. In terms of criteria based on the time delay and the code size, SA2pMP is demonstrated feasible for implementation in Java ME enabled CLDC-1.1 mobile devices.

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)0.002
metaresearch head score (Gemma)0.005
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.062
GPT teacher head0.350
Teacher spread0.288 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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