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Record W2022302485 · doi:10.1145/1655008.1655012

Browser interfaces and extended validation SSL certificates

2009· article· en· W2022302485 on OpenAlexaff
Robert Biddle, Paul C. van Oorschot, Andrew S. Patrick, Jennifer Sobey, Tara Whalen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpam and Phishing Detection
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceThe InternetUSableCertificateUsabilityWorld Wide WebPublic key certificateUser interfaceInterface (matter)Computer securityHuman–computer interactionPublic-key cryptographyEncryptionOperating system

Abstract

fetched live from OpenAlex

There has been a loss of confidence in the security provided by SSL certificates and browser interfaces in the face of various attacks. As one response, basic SSL server certificates are being demoted to second-class status in conjunction with the introduction of Extended Validation (EV) SSL certificates. Unfortunately, EV SSL certificates may complicate the already difficult design challenge of effectively conveying certificate information to the average user. This study explores the interfaces related to SSL certificates in the most widely deployed browser (Internet Explorer 7), proposes an alternative set of interface dialogs, and compares their effectiveness through a user study involving 40 participants. The alternative interface was found to offer statistically significant improvements in confidence, ease of finding information, and ease of understanding. Such results from a modest re-design effort suggest considerable room for improvement in the user interfaces of browsers today. This work motivates further study of whether EV SSL certificates offer a robust foundation for improving Internet trust, or a further compromise to usable security for ordinary users.

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)0.016
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.017
GPT teacher head0.239
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations72
Published2009
Admission routes1
Has abstractyes

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