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Record W32836389

Pass-Go: A Proposal to Improve the Usability of Graphical Passwords

2008· article· en· W32836389 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsUniversity of OttawaWilfrid Laurier University
Fundersnot available
KeywordsPasswordComputer scienceUsabilityScheme (mathematics)Cognitive passwordS/KEYPassword policyComputer securityHuman–computer interactionOne-time password
DOInot available

Abstract

fetched live from OpenAlex

Inspired by an old Chinese game, Go, we have designed a new graphical password scheme, Pass-Go, in which a user selects intersections on a grid as a way to input a password. While offering an extremely large full password space (256 bits for the most basic scheme), our scheme provides acceptable usability, as empirically demonstrated by, to the best of our knowledge, the largest user study (167 subjects involved) on graphical passwords, conducted in the fall semester of 2005 in two university classes. Our scheme supports most application environments and input devices, rather than being limited to small mobile devices (PDAs), and can be used to derive cryptographic keys. We study the memorable password space and show the potential power of this scheme by exploring further improvements and variation mechanisms.

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)0.000
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: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.192

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 science0.0010.000
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 head0.250
Teacher spread0.234 · 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

Quick stats

Citations194
Published2008
Admission routes1
Has abstractyes

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