MétaCan
Menu
Back to cohort
Record W2606547722 · doi:10.1109/icin.2017.7899400

Usable authentication systems for real time web-based audio/video communications

2017· article· en· W2606547722 on OpenAlexaff
Hassan Bostani, Jean‐Charles Grégoire

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsComputer scienceWebRTCUsabilityAuthentication (law)World Wide WebLoginCAPTCHAMultimediaHyperlinkOverhead (engineering)Computer securityWeb pageHuman–computer interactionOperating system

Abstract

fetched live from OpenAlex

User experience and general usability are getting more and more important in system development. Such concerns are especially highlighted when extra security features generate overhead which could easily lead to user frustration. The WebRTC <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> standard, as a new multimedia library, endows browsers with universal and stable real time multimedia communication, but it is lacking an authentication system. While it is possible to use common third party authentication services (e.g. from Google, Facebook), these solutions may be too constraining. We have developed a flexible authentication system for a Web-based multimedia communication system using the WebRTC library and the Google channel APIs. It features a user management framework which includes several scenarios of authentication including local as well as cloud-based authentication (e.g. Google and Facebook login). We present different authentication scenarios, and thereafter focus on a study to investigate the degree of usability of the solutions. We propose different authentication solutions for various degree of needs in security requirements in terms of level or user comfort and preferences.

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 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 categoriesScholarly communication
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 score0.957
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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0040.000
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 head0.046
GPT teacher head0.307
Teacher spread0.260 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicUser Authentication and Security SystemsFrench-language works237,207