MétaCan
Menu
Back to cohort
Record W2117459638 · doi:10.1109/icitst.2009.5402625

A rotary PIN entry scheme resilient to shoulder-surfing

2009· article· en· W2117459638 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 institutionsConcordia University
Fundersnot available
KeywordsComputer scienceComputer securityAuthentication (law)UsabilityScheme (mathematics)Identification (biology)Smart cardPoint (geometry)Human–computer interaction

Abstract

fetched live from OpenAlex

The combination of tokens or cards and personal identification numbers (PINs) are widely used for authentication in many applications including automatic teller machines (ATMs) and point of sales (POSs). Recent security incidents have shown that criminals can get these authentication tokens or cards either by pickpocketing or through fake magnetic card readers. Furthermore, PINs may also be captured through shoulder-surfing or by the use of concealed miniature cameras. Upon obtaining both authentication factors, criminals can easily break into users' accounts which presents a high security risk. In this paper, we propose a new spinwheel-like PIN entry scheme which is resilient against shoulder-surfing attacks even if the shoulder-surfer can record the entire PIN entry procedure for one time with a video device. This scheme has two variants, both of which achieve a good balance between security and usability.

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: none
Teacher disagreement score0.778
Threshold uncertainty score0.489

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 head0.018
GPT teacher head0.270
Teacher spread0.252 · 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

Citations12
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicUser Authentication and Security SystemsFrench-language works237,207