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Record W4234721009 · doi:10.22215/etd/2015-11139

PGP Auth: Using Public Key Encryption for Authentication on the Web

2015· dissertation· en· W4234721009 on OpenAlex
Derek Wueppelmann

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
Typedissertation
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsPasswordComputer scienceAuthentication (law)Computer securityMulti-factor authenticationSoftwareChallenge–response authenticationEncryptionChip Authentication ProgramEmail authenticationAuthentication protocolOperating system

Abstract

fetched live from OpenAlex

The majority of authentication systems use text passwords, as they provide a flexible method of authenticating on a wide variety of devices. Unfortunately, having suffi- ciently strong passwords does not protect users against phishing or offline guessing attacks. In this thesis, we present a new authentication mechanism that uses PGP. We iteratively designed PGP Auth, implemented it, and conducted user testing. Users rated the software highly and indicated that they would be very likely to use the software. They also liked the idea of having a single password to access their accounts and appreciated the security of using PGP as an authentication system. We believe that with a refined user interface, PGP Auth is a viable authentication mechanism that addresses many of the security vulnerabilities of traditional text password authentication. We also provide recommendations to aid in the development of future versions of PGP Auth based on our results.

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 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 score0.895
Threshold uncertainty score0.770

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 communication0.0010.000
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 head0.120
GPT teacher head0.334
Teacher spread0.214 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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