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Record W2037193857 · doi:10.1145/1993060.1993062

Homogeneous physio-behavioral visual and mouse-based biometric

2011· article· en· W2037193857 on OpenAlexaff
Omar Hamdy, Issa Traoré

Bibliographic record

VenueACM Transactions on Computer-Human Interaction · 2011
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBiometricsComputer sciencePasswordWord error rateArtificial intelligenceKeystroke dynamicsHomogeneousClassifier (UML)Pattern recognition (psychology)Computer visionMachine learningData miningComputer securityMathematics

Abstract

fetched live from OpenAlex

In this research, we propose a novel biometric system for static user authentication that homogeneously combines mouse dynamics, visual search capability and short-term memory effect. The proposed system introduces the visual search capability, and short-term memory effect to the biometric-based security world for the first time. The use of a computer mouse for its dynamics, and as an input sensor for the other two biometrics, means no additional hardware is required than the standard mouse. Experimental evaluation showed the system effectiveness using variable or one-time passwords. All of these attributes qualify the proposed system to be effectively deployed as a static authentication mechanism. Extensive experimentation was done using 2740 sessions collected from 274 users. To measure the performance, a computational statistics model was specially designed and used; a statistical classifier based on Weighted-Sum produced an Equal Error Rate (EER) of 2.11%.

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)0.001
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.066
GPT teacher head0.313
Teacher spread0.247 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

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Same venueACM Transactions on Computer-Human InteractionSame topicUser Authentication and Security SystemsFrench-language works237,207