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Record W2469489329

Who Are You? It Depends (On What You Ask Me!): Context-Dependent Dynamic User Authentication

2016· article· en· W2469489329 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

VenueSymposium On Usable Privacy and Security · 2016
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceAuthentication (law)Context (archaeology)Ask priceObject (grammar)Computer securityWorld Wide WebHuman–computer interactionArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Traditionally, the approaches to user authentication have been more static, which have often proved to be less secure. More recently, some researchers [3] have explored allowing users to choose one of several available authentication schemes. In the recent past, researchers have also considered context-dependent attributes in user authentication. Context is information that allows a system to “characterize the situation of an entity, where an entity can be a person, place, or physical, or computational object” [4]. Using context-dependent attributes makes a system more dynamic and adaptive; it makes it possible for systems to associate levels of trust with user actions to grant access to requested resources [1] and to design adaptive systems to authenticate users based on their location and other attributes [5].

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.014
GPT teacher head0.251
Teacher spread0.237 · 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